Dissertations / Theses on the topic 'Aggregation'

Neutrophil aggregation has been widely evaluated from changes in light transmission. Using direct particle counting, we demonstrated that light transmission does not accurately reflect aggregation, and showed that in contrast to previous reports, newborn neutrophils do not aggregate irreversibly. We developed a flow cytometric technique to measure the kinetics of neutrophil aggregation, including latent times for onset of aggregation, initial forward and reversal rates, and maximal extents of aggregation. The kinetics of neutrophil aggregation were related to changes in initial cell concentration, stir speed (shear), and activator type and concentration. Physiologic activators stimulated reversible aggregation, accompanied by an exponential decay in aggregatory potential with increasing time. The fraction of occupied activator receptors was found to correspond to the fraction of maximal rates or extent of aggregation. Monoclonal antibodies were used to show that neutrophil aggregation is mediated by the Mac-1 integrin (CD11b/CD18). Direct measurements of aggregation have enhanced our understanding of the (patho)physiologic process of neutrophil aggregation.

This thesis is an empirical comparison of the relationship between money and other key economic variables and investigates an alternative method of defining money in Canada. Severe theoretical problems with traditional monetary aggregation methods are identified and Divisia aggregates are examined through the use of index number and aggregation theory. Summation and Divisia aggregates are constructed, tested and compared in three critical areas: information content, causality and stability. In particular this thesis investigates whether Divisia money is a potentially useful indicator of economic conditions. The data consists of Canadian quarterly observations for the period 1968.1 to 1989.4 for 26 different monetary assets and their own rates of return. The Divisia indices do not clearly outperform their summation counterparts but do show consistent and stable growth trends during the period in question. The results show that Divisia monetary aggregation is theoretically more appealing than the simple sum approach and that Divisia money provides meaningful information for Canadian monetary policy.

In this dissertation, I discuss two distributive principles in moral philosophy: Derek Parfit's Prioritarianism and Egalitarianism. I attempt to defend a version of Egalitarianism, which I call Weighted Egalitarianism. Although Parfit claims that Egalitarianism is subject to what he calls the Levelling Down Objection, I show (a) that my proposed Weighted Egalitarianism is not subject to the Objection, and (b) that it gives priority to the worse off people. The real difference between the two principles lies in how the weight of each person's well-being is determined. Prioritarianism assumes that there is a moral scale of the goodness of well-being, independently of distributions of people's well-being. I raise two objections to this claim: firstly, it is hard to believe that the choice of the level of well-being affects our distributive judgement; secondly, it is hard to believe that there is such a moral scale independently of distributions of people's well-being. On the other hand, Weighted Egalitarianism claims that the weight is given by the rank order position of the person in the ranking by well-being level. This means that, in Weighted Egalitarianism, the goodness of a distribution is an increasing, linear function of people's well-being. Weighted Egalitarianism is not affected by the choice of the level of people's well-being. Nor does it require require the moral scale of the goodness of well-being independently of distributions of people's well-being. Leximin, which might be a version of Prioritarianism, avoids my objections. But it is hard to support Leximin, because it rules out the trade off between the better off and the worse off. I conclude that Weighted Egalitarianism is more acceptable than Prioritarianism.

Deep eutectic solvents (DESs) have attracted significant attention for a wide range of applications including metal deposition, natural product extraction, metal recycling and catalysis. In general they are good at solubilising polar and charged solutes and hence their properties can be tuned. This study aims to investigate how the properties of DESs can be modified by the addition of surfactants. One aim is to understand how and why surfactants aggregate and how their surface activity differs from aqueous solutions. Firstly, the physical properties of three DESs are characterised containing different surfactants. The critical micelle concentrations, CMC are analysed together with the extent of aggregation. It was found that CMC values of SDS in Reline and Glyceline are smaller than in aqueous systems while in Ethaline the value are similar to those in water. Dynamic light scattering and viscosity data show that supramolecular aggregates of SDS in Ethaline change from cylindrical to liquid crystalline phases at about 3 times the CMC concentration. Moreover, the thermodynamic parameters of the micellization indicated that SDS aggregation was enthalpy controlled. The pattern of the micelle aggregation was different to that observed in water. Surfactant aggregates are found to form despite the high ionic strength due to that large choline cations having a low charge density. The interface properties of surfactants were studied and it was found that the aggregation was favoured in media with a higher surface energy as this disfavoured the solubilisation of monomers. The surfactants were found to be less surface active than they were in aqueous solutions. This was proposed to be due to the high ionic strength of the DESs meaning that charge-charge interactions between the interface and the surfactant were less important. The implication of this is demonstrated when surfactants were tested as brighteners in copper electroplating solutions. It was found that surfactants did not affect the deposit morphology as significantly as molecules which specifically adsorbed on the copper surface which indicated the method by which brighteners functioned in DESs was not primarily through charge-charge interactions.

The most thermodynamically stable biological structure is the cross-beta secondary structure of the "amyloid"or "prion". As a testament to its stability, the amyloid occurs naturally in 2 rare instances: as a mechanism to protect or destroy life. Pathogenic amyloids are the signature of neurological disorders such as Alzheimer's and Parkinson's disease and bovine spongiform encephalopathy (BSE), which have no effective treatments or known cures. Pathogenic amyloids appear as nanometer sized "plaques" that self-assemble over time. The plaques usually are well-organized crystalline/fibrous structures ~10-20 nm in diameter and >100 nm long. "Functional" amyloids are very rare in nature and serve the direct purpose to proliferate life. Stalks to protect eggs, fibers to coat spores, and adhesive proteins of bacteria, algae, fungi, and mollusks are examples. Functional amyloids can be larger than pathogenic amyloids by 1-2 orders of magnitude. There is a burgeoning research field based on emulating the amyloid. This is because it can be formed from a host of proteins or peptides simply by denaturing them enough to form a cross-beta secondary structure and has a modulus of >10 GPa. As a general reference, "protein" is usually a very high molecular weight, naturally occurring molecule and "peptide" is a much smaller portion of a natural protein or a non-natural molecule synthesized from a few amino acids. Researchers are increasingly attempting to take advantage of the functional amyloid. It is still not understood how the functional amyloid self-assembles or why it can be larger than the pathogenic amyloid. We have identified a potential pathway to large functional amyloids that involves a long alpha-helix containing protein (the "adder") undergoing an alpha to beta transition in the presence of a hydrophobic beta-sheet template. Testing our hypothesis against proteins found in natural large functional amyloids seems to suggest it is a ubiquitous process. The resulting material is a fiber composite similar to the native structures.<br>Master of Science

Thesis (Ph. D.)--Ohio State University, 2003.<br>Title from first page of PDF file. Document formatted into pages; contains xii, 135 p.: ill. Includes abstract and vita. Co-advisors: Peter D. Easton and Kirk L. Philipich, Dept. of Accounting and Management Information Systems. Includes bibliographical references (p. 127-135).

Temporal database systems extend relational database systems to support time-varying information. One important such extension is support for time-varying aggregate functions, such as a time-varying average. Our research will show that temporal aggregates may be specified in a semantically well defined manner yet be efficiently implemented as simple extensions to relational databases. We introduce a taxonomy of temporal aggregation, based on a study of all major temporal query languages containing aggregates. The taxonomy categorizes the expressiveness and functionality of temporal aggregation. Based on this taxonomy, we introduce extensions to TSQL2 for temporal aggregation. The proposed language constructs allow one to express the variety of features identified in the taxonomy. We briefly discuss the semantics for the temporal aggregate language extension. We introduce an operator for evaluating temporal aggregates in a temporal relational algebra; the operator was designed to implement the tuple semantics. We show that theoretically, the most efficient evaluation of a temporal aggregate over a relation with n unique timestamps requires Θ(n log n) time, with O(n log n) space in any decision tree algorithm. We provide an example algorithm meeting these requirements, utilizing a 2-3 tree. Based on the requirements for evaluation of the algebraic operator, we introduce a series of main memory algorithms for evaluating temporal aggregates, including the aggregation tree, k-ordered aggregation tree, the chalkboard algorithm, the linked-list algorithm, and show how to perform aggregation using a 2-3 tree. The algorithms exhibit different applicability depending on aspects of the input relation, including sort order, percentage of long-lived tuples, and number of tuples. We also provide an algorithm which executes using only a user-limited amount of memory, the paging aggregation tree. We characterize the effectiveness of these algorithms based on an empirical study of their performance.

As wireless communications is becoming an increasingly important part of ourevery day lives, the amount of transmitted data is constantly growing, creating ademand for ever-increasing data rates. One of the technologies used for boostingdata rates is carrier aggregation, which allows for wireless units to combine multipleconnections to the cellular network. However, there is a limited number ofpossible combinations defined, meaning that there is a need to search for the bestcombination in any given setup. This thesis introduces software capable of organizingthe defined combinations into tree structures, simplifying the search foroptimal combinations as well as allowing for visualizations of the connectionspossible. In the thesis, a proposed method of creating these trees is presented,together with suggestions on how to visualize important combination characteristics.Studies has also been made on different tree traversal algorithms, showingthat there is little need for searching through all possible combinations, but thata greedy approach has a high performance while substantially limiting the searchcomplexity.<br>I samband med att trådlösa kommunikationssystem blir en allt större del av våraliv och mängden data som skickas fortsätter att stiga, skapas en efterfrågan förökade datatakter. En av teknologierna som används för att skapa högre datatakterär bäraraggregering (carrier aggregation), som möjliggör för trådlösa enheteratt kombinera flertalet uppkopplingar mot det mobila nätverket. Det finns dockbara ett begränsat antal kombinationer definierade, vilket skapar ett behov av attsöka upp den bästa kombinationen i varje givet tillfälle. Detta arbete introducerarmjukvara som organiserar dessa kombinationer i trädstrukturer, vilket förenklarsökning efter optimala kombinationer tillsammans med möjligheten att visualiserade potentiella uppkopplingarna. I arbetet presenteras en föreslagen metodför att skapa dessa träd, tillsammans med uppslag på hur viktiga egenskaperhos kombinationerna kan visualiseras. Olika trädsökningsalgoritmer har ocksåundersökts, och det visas att det inte är nödvändigt att söka igenom hela träd.Istället visar sig giriga algoritmer ha hög prestanda, samtidigt som sökstorlekenkan hållas kraftigt begränsad.

Locust swarms cause famine and hunger in parts of Sub-Saharan Africa as they travel across croplands and eat vegetation. Current models start with biological properties of locusts and analyze the macroscopic behavior of the system. These models exhibit the desired migratory behavior, but do so with too many parameters. To account for this, a new model, the Alignment and Intermittent Motion (AIM) model, is derived with minimal assumptions. AIM is constructed with regards to locust biology, allowing it to elicit biologically correct locust behavior: the most noteworthy being the fingering of hopper bands. A Particle-in-Cell method is used to optimize simulations, allowing for trials of up to 106 particles over reasonable timescales. We analyze the shapes of these swarms, note the similarities between simulations of large and small swarms, and propose possible methods for analyzing simulation metrics.

Thesis (M.S.)--Texas A&M University, 2003.<br>"Major Subject: Industrial Engineering" Title from author supplied metadata (automated record created on Jul. 18, 2005.) Vita. Abstract. Includes bibliographical references.

Over the last few years, the cost of energy from renewable resources, such as sunlight and wind, has declined resulting in an increasing use of Renewable Energy Sources (RES). As a result, the energy produced by RES is fed into the power grid while their share is expected to significantly increase in the future. However, RES are characterized by power fluctuations and their integration into the power grid might lead to power quality issues, e.g., imbalances. At the same time, new energy hungry devices such as heat-pumps and Electric Vehicles (EVs) become more and more popular. As a result, their demand in power, especially during peak-times, might lead to electrical grid overloads and congestions. In order to confront the new challenges, the power grid is transformed into the so-called Smart Grid. Major role in Smart Grid plays the Demand Response (DR) concept. According to DR, Smart Grid better matches energy demand and sup- ply by using energy flexibility. Energy flexibility exists in many individual prosumers (producers and/or consumers). For instance, an owner of an EV plugs-in his EV for more time than it is actually needed. Thus, the EV charging can be timely shifted. The load demanded for charging could be moved to time periods when production from wind turbines is high or away from peak-hours. Thus, RES share is increased and/or the electrical grid operation is improved. The Ph.D. project is sponsored by the Danish TotalFlex project (http://totalflex.dk). Main goal of the TotalFlex project is to design and establish a flexibility market framework where flexibility from individual prosumers, e.g., household devices, can be traded among different market actors such as Balance Responsible Parties (BRPs) and distribution system operators. In order for that to be achieved, the TotalFlex project utilizes the flex-offer concept. Based on the flex-offer concept, flexibility from individual prosumers is captured and represented by a generic model. However, the flexible loads from individual prosumers capture very small energy amounts and thus cannot be directly traded in the market. Therefore, aggregation becomes essential. The Ph.D. project focuses on developing aggregation techniques for energy flexibilities that will provide the opportunity to individual prosumers to participate in such a flexibility market. First, the thesis introduces several flexibility measurements in order to quantify the flexibility captured by the flex-offer model and compare flex- offers among each other, both on an individual and on an aggregated level. Flexibility is both the input and the output of the aggregation techniques. Aggregation techniques aggregate energy flexibility to achieve their goals and, at the same time, they try to retain as much flexibility as possible to be traded in the market. Thus, second, the thesis describes base-line flex-offer aggregation techniques and presents balance aggregation techniques that focus on balancing out energy supply and demand. Third, since there are cases where electrical grid congestions occur, the thesis presents two constraint-based aggregation techniques. The techniques efficiently aggregate large amounts of flex-offers taking into account physical constraints of the electrical grid. The produced aggregated flex-offers are still flexible and when scheduled, a normal grid operation is achieved. Finally, the thesis examines the financial benefits of the aggregation techniques. It introduces flex-offer aggregation techniques that take into account real market technical requirements. As a result, individual small flexible loads can be indirectly traded in the energy market through aggregation. The proposed aggregation techniques for energy flexibilities can con- tribute to the use of flexibility in the Smart Grid in both current and future market frameworks. The designed techniques can improve the services offered to the prosumers and avoid the very costly upgrades of the distribution network.<br>Gennem de senere år er prisen faldet på energi fra vedvarende energikilder såsom sollys og vind, hvilket har medført et stigende forbrug af vedvarende energi. Dette har resulteret i, at energi, der produceret af vedvarende energi, sendes ud i elnettet og andelen forventes at stige markant i fremtiden. Vedvarende energi er imidlertid karakteriseret af effektsvingninger, og integrationen i elnettet kan føre til kvalitetsproblemer med strømmen som for eksempel uligevægt. Samtidig bliver enheder, der sluger vedvarende energi såsom varmepumper og elektriske køretøjer, mere og mere populære. Dette resulterer i, at efterspørgslen på energi, især i spidsbelastede situationer, kan medføre overbelastning og trængsel på elnettet. For at konfrontere de nye udfordringer bliver elnettet ændret til et såkaldt Smart Grid. Konceptet om udbud og efterspørgsel Demand Response (DR) spiller her en meget stor rolle. Ifølge DR, imødegår Smart Grid bedre udbud og efterspørgsel af energi ved at bruge fleksibel energi. Fleksibel energi eksisterer i mange individuelle producenter og/eller forbrugere. For eksempel tilslutter en ejer af et elektrisk køretøj sit køretøj i mere tid end det rent faktisk er nødvendigt. På denne måde kan tidspunktet for opladningen ændres rettidigt. Belastningen, der kræves for opladning, kunne flyttes til perioder, hvor produktion fra vindmøller er høj eller væk fra de spidsbelastede tidspunkter. Således øges vedvarende energi’ andel og/eller elnettets drift er forbedret. Dette Ph.D. projekt er sponsoreret af det danske TotalFlex projekt (http://totalflex.dk). TotalFlex’ formål er at designe og etablere et fleksibelt elmarkedsystem, hvor fleksibilitet fra individuelle producent og/ eller forbruger f.eks. husholdningsenheder kan blive udvekslet mellem forskellige markedsaktører såsom balanceansvarlige parter og eldistributionsnettets operatører. For at opnå dette, udnytter TotalFlex flex-offer konceptet. Baseret på konceptet om flex-offer, bliver fleksibilitet fra individuelle prosumers fanget og repræsenteret i en generisk model. Fleksible belastninger fra de individuelle prosumers fanger imidlertid kun meget små energimængder og kan ikke udveksles direkte på markedet. Derfor bliver aggregering essentielt. Ph.D. projektet fokuserer på at udvikle aggregering-steknikker for energifleksibilitet, der kan give individuelle prosumers mulighed for at deltage i et sådant fleksibilitetsmarked. Først vil afhandligen introducere adskillige fleksibilitetsmålinger for at kvantificere fleksibiliteten, der fanges af flex-offer modellen og sammenligne flex-offer med hinanden både på et individuelt og et aggregeret niveau. Input og output af aggregeringsteknikker er fleksibilitet. Aggregeringsteknikker samler energifleksibilitet for at opnå dets mål og forsøger på samme tid at beholde så meget fleksibilitet som muligt til at blive udvekslet på markedet. Herpå forsøger afhandligen for det andet at beskrive basis flexoffer aggregeringsteknikker og præsenterer balance-aggregeringsteknikker, der fokuserer på at afbalancere energiudbud og -efterspørgsel. Siden der er situationer, hvor overbelastninger af elnettet forekommer, præsenterer afhandlingen for det tredje, to begrænsningsbaserede aggregeringsteknikker. Teknikkerne samler effektivt store mængder af flex-offers og tager samtidig hensyn til fysiske begrænsninger i elnettet. De producerede, samlede flexoffers er stadig fleksible og efter det er planlagt, opnås et normaltfungerende net. Til slut vil afhandlingen undersøge de økonomiske fordele ved aggregeringsteknikkerne. Den introducerer flex-offer aggregeringsteknikkerne, der tager højde for de reelle, tekniske krav, der er på markedet. Resultatet kan være, at individuelle små fleksible belastninger indirekte kan udveksles på energimarkedet gennem aggregering. De foreslåede aggregeringsteknikker til energi-fleksibilitet kan bidrage til brug af fleksibilitet i Smart Grid i både nuværende og fremtidige markedsrammer. De designede teknikker kan forbedre de tilbudte ydelser til prosumers og undgå de meget dyre opgraderinger af distributionsnetværk<br>Durante los últimos años, la bajada en el precio de la energía procedente de fuentes renovables, tales como luz solar y eólica, ha resultado en un aumento del uso de este tipo de recursos de Energía Renovables (ER). Como consecuencia de este aumento, la energía producida a través de ER es inyectada en la red eléctrica y se espera que la proporción de energía suministrada a la red crezca significativamente en los próximos años. Sin embargo, las ER se caracterizan por ser muy fluctuantes y su integración en la red eléctrica podría acarrear problemas de calidad, como por ejemplo desequilibrios energéticos. Al mismo tiempo, nuevos dispositivos de alto consumo de energía, como bombas de calor y vehículos eléctricos, son cada vez mas populares y la alta demanda de estos, especialmente en horas puntas, puede crear sobrecargas y congestiones en la red. Para afrontar estos restos, la red eléctrica se transforma en la llamada Red Inteligente, dónde el concepto de respuesta a la demanda juega un papel. Esta thesis de doctorado está patrocinada por el proyecto danés TotalFlex (http://totalflex.dk). El objetivo principal de este proyecto es diseñar y establecer el marco de flexibilidad de mercado, dónde la flexibilidad de productores/consumidores, por ejemplo los dispositivos del hogar, pueda ser comercializada entre los diferentes actores del mercado como las comercializadoras de electricidad y los operadores de sistemas de distribución. Para lograr este propósito, el proyecto TotalFlex utiliza el concepto flex-offer flexibilidad en la oferta. Basado en el concepto flex-offer, la flexibilidad de consumidores y productores individuales es capturada y representada a través de un modelo genérico. Sin embargo, las cargas flexibles de estos individuos producen pequeñas cantidades de energía y, por lo tanto, no pueden ser directamente negociadas en el mercado. Esto significa que la agregación de esta energía es esencial. Este Ph.D está enfocado desarrollo de técnicas de agrega para que permitirán a productores y consumidores individuales participar en dicha. En primer lugar, esta tesis introduce medidas de flexibilidad con la finalidad de cuantificar la flexibilidad calculada por el modelo flex-offer y comparar las diferentes ofertas entre ellas, tanto a nivel individual como agregado. Flexibilidad es tanto la entrada como la salida de las técnicas de agregado, las cuáles agregan flexibilidad energética para lograr sus objetivos y, al mismo tiempo, retener la máxima flexibilidad para comerciarla en el mercado. En segundo lugar, la tesis describe la base de las tecnicas de agregado flex-offer y presenta técnicas de que se enfocan en un balance entre la oferta y la demanda energética. Tercero, dado que existen casos dónde se producen congestiones en la red eléctrica, la tesis presenta tecnicas de agregado basadas en restricciones. Dichas técnicas agregan grandes cantidades de flex-offers considerando restricciones físicas de la red eléctrica. Las flexoffers agregadas que se producen son aún flexibles y, cuando se programan, se logra una operación normal de red. Por último, en la tesis se examina los beneficios económicos de las técnicas agregadas, introduciendo técnicas de agregado flex-offer que tienen en cuenta los requisitos técnicos del mercado real. Como resultado, las pequeñas cargas individuales y flexibles pueden ser indirectamente negociadas en el mercado energético a través de la agregación. Las técnicas de agregado propuestas para favorecer la flexibildad energética puede contribuir al uso de flexibilidad en la red inteligente tanto en el presente como en el futuro. Mejorar los servicios ofrecidos a consumidores y productores así como evitar las costosas actualizaciones de la red de distribución.

In the field of artificial intelligence, recommender systems are methods for predicting the relevance items to a users. The items can be just about anything, for example documents, articles, movies, music, events or other users. Recommender systems examine data such as ratings, query logs, user behavior and social connections to predict what each user will think of each item.Modern recommender systems combine multiple standard recommenders in order to leverage disjoint patterns in available data. By combining different methods, complex predictions that rely on much evidence can be made. These aggregations can for example be done by estimating weights that result in an optimal combination.However, we posit these systems have an important weakness. There exists an underlying, misplaced subjectivity to relevance prediction. Each chosen recommender system reflects one view of how users and items should be modeled. We believe the selection of recommender methods should be automatically chosen based on their predicted accuracy for each user and item. After all, a system that insists on being adaptive in one particular way is not really adaptive at all.This thesis presents a novel method for prediction aggregation that we call adaptive recommenders. Multiple recommender systems are combined on a per-user and per-item basis by estimating their individual accuracy in the current context. This is done by creating a secondary set of error estimating recommenders. The core insight is that standard recommenders can be used to estimate the accuracy of other recommenders. As far as we know, this type of adaptive prediction aggregation has not been done before.Prediction aggregation (combining scores) is tested in a recommendation scenario. Rank aggregation (sorting results lists) is tested in a personalized search scenario. Our initial results are promising and show that adaptive recommenders can outperform both standard recommenders and simple aggregation methods. We will also discuss the implications and limitations of our results.

It has been proved from several studies that the genetic influence has been the most significant factor for having preeclampsia (PE). Still there are many uncertainties about origin and magnitude of the genetic effects as no specific inheritance patterns have been established. In this study, heritage risk of PE is in both the woman’s family and her partner’s family to her risk of PE is examined, along women and men own history with same and different partners. Moreover it is also examined whether timing of onset of PE is also has any impact on familial clustering of PE. Here, we used the population based Danish birth and multi generation registers to identify a cohort of women who have given birth during 1978 to 2008; which consisted of 1,79,69,28 singleton deliveries. This information is linked with pedigree information from the Danish Family Relation Database to define both maternal and paternal relationships. Risk ratios were estimated comparing women with and without various PE histories. It is found that the recurrence risk of a woman suffering from PE is 12.4 with 95% confidence limits (11.9, 12.8). Woman's recurrence risk diminishes only slightly when she changes partner means that particularly maternal genetic factors play the largest role, compared to male partner whose recurrence risk almost diminishes if he changes his female partner. Women and men from families with PE contribute to risk of PE in pregnancies they are involved in. The woman’s family history is still more important compared to man family history of PE; except for increased rick in pregnancies fathered by men who were born to preeclamptic mothers.  The recurrence risk of a women suffering from PE, if she already has suffered from this condition before 34 weeks is found to be very high (RR=25.4 with 95% confidence limits (21.8, 29.1)) with same male partner. It is found that early-onset PE and later-onset varieties have a clear genetic component but the intensity of early onset is stronger than late onset varieties. There are both maternal and paternal genetic contributions to early-onset PE, with the maternal ones seeming to be stronger.

The aggregation behaviour of sphalerite suspension and the role of zinc and magnesium ions are investigated. Aggregation is monitored by suspension analysis (turbidity) and optical microscopy and, in particular, a conductivity-settling technique. To probe the mechanisms, electrophoretic mobility (zeta potential) measurements and field emission scanning electron microscopy (FE-SEM) imaging are used.<br>In the case of sphalerite alone, for samples from a variety of sources, aggregation occurred at pH 8--10, well above the range in iso-electric point (pH 2--6). The aggregation is attributed to the presence of Zn(OH) 2, the dominant species over this pH range. To test whether zinc hydrolysis products promote aggregation silica and chalcopyrite suspensions were doped with Zn2+ ions; aggregation over the same pH range was found. This observation is similar to that of Healy and Jellet (1967) for zinc oxide, ZnO. They suggested aggregation was due to release of Zn2+ ions to form Zn(OH)2 which polymerizes and flocculates the particles. The same mechanism is proposed for sphalerite.<br>Aggregation due to magnesium ions was determined using the settling rate of sphalerite and silica suspensions (individually) as a function of Mg 2+ concentration, pH and suspension density (%v/v solids). Aggregation at pH > 10 was found for both minerals corresponding to magnesium hydroxide. However, the mineral's response to the three variables suggests the mechanism for each is different. The proposed mechanism of aggregation by Mg(OH) 2 for sphalerite is chemical bridging and for silica, electrostatic bridging. Electrostatic bridging is revealed by aggregation passing through a maximum as a function of both coagulant concentration and pH. For sphalerite, while there is a maximum with [Mg2+] (Mg2+ concentration) there is none with pH (after allowing for the self-aggregation of sphalerite). Further, electrostatic bridging requires surface patches of the bridging material (Mg(OH)2) and the FE-SEM images showed no such evidence. The interpretation for silica aggregating with Mg2+ follows that proposed by Krishnan and Iwasaki (1986). The pH, [Mg2+] and solid concentration effects are compatible with electrostatic bridging, as is the morphology as hydroxide patches were identified by FE-SEM.<br>In certain cases the conductivity-settling data suggested the particles were more conductive than the liquid. The conductivity-settling technique was adapted to measure the electrical conductivity of particles dispersed in water. The conductivity was estimated at the iso-conductivity point where the solution and the particles have the same conductivity. The technique was tested on chalcocite, chalcopyrite, galena, pyrite and sphalerite. The order of mineral conductivity followed that of their electrochemical rest potential, as expected. It is observed that the adsorption of xanthate significantly reduced the conductivity of chalcopyrite and copper activation increased the conductivity of sphalerite but treatment with lead had no effect.

In nature, bacteria usually exist as aggregates, in order to withstand changes in environmental conditions. Bacterial aggregation is of great significance in the field of biotechnology, environmental studies and medicine. Bacterial aggregation is thought to be governed by physical forces such Van der Waals and electrostatic interaction. However, extracellular polymeric substances (EPS), and the ability. of bacteria ·to participate in cell-to-cell communication via quorum sensing molecules have also been implicated in the bacterial aggregation. process. Despite the wealth of knowledge available, a detailed understanding of bacterial aggregation still remains unclear. The overall aim of this work therefore, is to understand bacterial aggregation at the cellular and sub-cellular level using existing colloidal characterisation techniques and post genomic methods. This will enable both the biological and the physical aspects of aggregation to be studied together. E.coli strains (AB1157, MG1655 and MG1655 luxS) were cultivated in Luria-Bertani (LB) medium at 30°C supplemented with or without 0.5 w/v (%) glucose at the beginning of growth phase. Depletion aggregation studies were carried out using E.coli AB1157 and E.coli MG1655 harvested at different growth phases using a nonadsorbing polymer, sodium polystyrene sulphonate (SPS) and biological produced extracellular polymeric substances (EPS) respectively. The content of EPS produced by E.coli MG1655 during their growth in different media w~s quantified and characterized using Fourier transformation infrared spectroscopy (FTIR), SDS-PAGE and an electrospray ionization-tandem mass spectrometry. The changes in cell surface properties of E.coli strains during growth, changes in media composition and quorum sensing were elucidated using potentiometric titration, FTIR and electrophoretic mobility. Neither quorum sensing, nor the addition of 0.5 w/v (%) glucose affected the growth pattern for the strains. However, the addition of 0.5 w/v (%) glucose to the medium affected the measurable amount of quorum sensing molecule present in the supernatant. Aggregation of E. coli was found to be dependent on the concentration and type of polymer used, as well as the surface chemistry of the cell. The cell surface functional groups, such as such as, hydroxyl, phosphoryl, amines and carboxylate groups varied with respect to different growth phase and changes in media. The protein content of free-EPS was found to significantly increase due to changes in growth phase and media composition. The growth phase, changes in media and quorum sensing all affected the cell surface properties and hence played a role in the aggregation capability of E.coli.

Fluorescent techniques are amongst the methods used to study the self assembly of proteins into oligomers, however, most of the reports in literature use extrinsic fluorophores to obtain information on the peptide system. The goal of this thesis is to demonstrate how the intrinsic Tyrosine fluorescence of the β-amyloid peptide can be used to monitor its own aggregation with, therefore, minimal interference on the peptide's native structure, its biochemistry and its spontaneous process of aggregation. Firstly, it is shown that the fluorescence of amino acid Tyrosine, naturally present in wild type β-amyloid, responds to the spontaneous aggregation of the peptide. This is achieved by performing time-correlated single-photon counting experiments during the process of the peptide's aggregation into amyloid fibrils. Through comparison with the well established Thioflavin T assay is also demonstrated that Tyrosine decay responds to changes caused by peptide aggregation well before the appearance of the characteristic β- sheet structures present in the fibrils. Then the use of β-amyloid's intrinsic Tyrosine amino acid as a sensor for the pre- brillar stages of aggregation is further tested and researched through a series of experiments with different initial β-amyloid concentrations. Patterns of consistent behaviour are found confirming that Tyrosine can act as a sensor for the formation of oligomers and kinetic information about the oligomerisation process is retrieved. Using this approach a comparison between the oligomerisation kinetics of the two most common variants of β-amyloid is performed. In the process of studying Tyrosine response to the peptide aggregation the accuracy of the discrete exponential decay model used to describe the decays is debated. A model-free analysis is used to study Tyrosine decay photophysics in the β-amyloid peptides throughout the process of aggregation. It is found that Tyrosine decay is a composition of four discrete decay components suggesting the existence of four rotameric forms of the amino acid in the Fluorescent techniques are amongst the methods used to study the self assembly of proteins into oligomers, however, most of the reports in literature use extrinsic uorophores to obtain information on the peptide system. The goal of this thesis is to demonstrate how the intrinsic Tyrosine uorescence of the β-amyloid peptide can be used to monitor its own aggregation with, therefore, minimal interference on the peptide's native structure, its biochemistry and its spontaneous process of aggregation. Firstly, it is shown that the uorescence of amino acid Tyrosine, naturally present in wild type β-amyloid, responds to the spontaneous aggregation of the peptide. This is achieved by performing time-correlated single-photon counting experiments during the process of the peptide's aggregation into amyloid brils. Through comparison with the well established Thioavin T assay is also demonstrated that Tyrosine decay responds to changes caused by peptide aggregation well before the appearance of the characteristic - sheet structures present in the brils. Then the use of β-amyloid's intrinsic Tyrosine amino acid as a sensor for the pre- brillar stages of aggregation is further tested and researched through a series of experiments with different initial β-amyloid concentrations. Patterns of consistent behaviour are found con rming that Tyrosine can act as a sensor for the formation of oligomers and kinetic information about the oligomerisation process is retrieved. Using this approach a comparison between the oligomerisation kinetics of the two most common variants of β-amyloid is performed. In the process of studying Tyrosine response to the peptide aggregation the accuracy of the discrete exponential decay model used to describe the decays is debated. A model-free analysis is used to study Tyrosine decay photophysics in the β-amyloid peptides throughout the process of aggregation. It is found that Tyrosine decay is a composition of four discrete decay components suggesting the existence of four rotameric forms of the amino acid in the -amyloid peptides. The ndings are further corroborated by molecular dynamic simulations, breaking with the traditional model of three rotameric forms for the uorescent amino acids in protein chains. Finally, the sensing method is used to study the inuence of external uorophores, both associating and covalently bound, on the process of oligomerisation. β-amyloid peptides. The findings are further corroborated by molecular dynamic simulations, breaking with the traditional model of three rotameric forms for the fluorescent amino acids in protein chains. Finally, the sensing method is used to study the inuence of external uorophores, both associating and covalently bound, on the process of oligomerisation.

On-line analytical processing (OLAP) provides multidimensional data analysis to support decision making. OLAP queries require extensive computation based on aggregation along many dimensions and hierarchies. The time required to process these queries has traditionally prevented the interactive analysis of large databases and in order to accelerate query-response time, precomputed results are often stored as materialised views for later retrieval. This adds a prohibitive storage overhead when applied to the whole set of aggregates, known as the data cube. Storage space and computation time can be significantly reduced by partial computation. The challenge in implementing the data cube has been to select the minimum number of views for materialisation, while retaining fast query response time. This thesis makes significant contributions to this area by introducing the Low Redundancy (L-R) approach which provides the means for the selection, computation and storage of nonredu ndant aggregates. Firstly, through the introduction of a novel technique, redundant aggregates are identified thus allowing only distinct aggregates to be computed and stored. Secondly, further redundancy is identified and eliminated using a second novel technique which stores these distinct aggregates in a compact differential form. Novel algorithms were introduced to implement these techniques and provide a solution which is both scalable and low in complexity. Both techniques have been evaluated using real and synthetic datasets with experimental results, and have achieved significant savings in computation time and storage space compared to the conventional approach. Savings have been shown to increase as dimensionality increases. Existing techniques for implementing the data cube differ from the L-R approach but they can be integrated with it to achieve faster query-response time. Finally, the implications of this work reach beyond the area of OLAP to the fields of decision support systems, user interfaces and data mining.

An increasing number of diseases are associated with protein misfolding, one type of which results in the formation of amyloid fibrils. This research has addressed the hypothesis that all proteins can form amyloid fibrils and investigates what factors protect proteins from forming these macromolecular assemblies. Most analyses of the aggregation propensity of proteins have been limited to the properties of the amino acid sequence, thus fail to consider the roles that higher levels of organisation play in protecting polypeptides from misfolding. The (α/β)8 barrels are a common class of proteins and have never been shown to form amyloid fibrils. This thesis aims to elucidate the characteristics that prevent (α/β)8 barrels from misfolding using Escherichia coli dihydrodipicolinate synthase (DHDPS), a homotetrameric (α/β)8 barrel protein, as a model. It is widely accepted that the precursor of amyloid fibrils is a partially folded species. It is hypothesised in this thesis that the (α/β)8 barrel fold protects the protein against this partial unfolding. This was tested by generating a catalogue of site-directed mutants of DHDPS and screening each of these in a range of pHs and ionic strengths. Amorphous aggregation propensity was assessed by monitoring light scattering at 340 nm and β-sheet specific aggregation was assessed using ThT. Thermal stability was monitored using DSF and CD spectroscopy. Crystallography was used to assess tertiary and quaternary structures and in the cases where crystal structures were not obtained, kinetics was used as a proxy indicator of correct folding and monomeric association. CD spectroscopy was also used to investigate the secondary structure of the DHDPS variants and analytical gel permeation liquid chromatography and AUC were used to confirm quaternary structure. The stability and aggregation propensity of DHDPS and its variants were assessed under a range of pH and salt conditions. It was established through the characterisation of the wild-type protein that the predominant determinant of stability was, unsurprisingly, pH. This was a trend observed for all the variants described. Affinity tags were used during the course of this research to facilitate and expedite the production of the protein variants. The introduction of tags containing a polyhistidine motif to DHDPS significantly altered some biophysical properties. Whilst the secondary and quaternary structures were found to be similar to the wild-type enzyme, the catalytic properties were changed. In addition to this, the propensity to aggregate was altered. The full-length polyhistidine tags increased the propensity of DHDPS to form β-sheet-specific aggregate, although this did not result in the formation of amyloid fibrils for most of the variants. The Zyggregator algorithm was used to predict amino acid substitutions that would increase the aggregation propensity of DHDPS. It identified several amino acids, three of which were chosen for mutation and two of which were expressed in sufficient quantity for further study. DHDPS Q90L and A207V were characterised and the amino acid substitutions did not significantly alter the kinetic parameters of the enzyme. The crystal structure of A207V was solved and confirmed the results of the kinetic analysis demonstrating unchanged tertiary and quaternary structures. Both variants exhibited tertiary and quaternary structures similar to the wild-type enzyme, although Q90L contained more disorder than the wild-type enzyme. The thermal denaturation temperatures and aggregation propensities were also similar to wild-type, although the propensity for both variants to form β-sheet-specific aggregates was reduced. The combinatorial effects of Q90L, A207V and the polyhistidine tags were assessed. This revealed that whilst most biophysical properties were unaffected, the β-sheet-specific aggregation propensity for pET M11 and pET 151/D-TOPO DHDPS Q90L and pET M11 DHDPS A207V, were significantly increased compared to the wild-type enzyme. The evolutionary forces driving the association of the monomeric and dimeric subunits of DHDPS are undetermined. Investigation of two quaternary structure mutants (DHDPS Y107W and L197Y) revealed that the tetrameric nature of E. coli DHDPS is important for protein activity, stability and the prevention of aggregation. The combinatorial affects of the disrupted quaternary structure and the polyhistidine tags further increased the predisposition of DHDPS to form β-sheet-specific aggregates, resulting in the formation of linear aggregates with some characteristics of amyloid fibrils. The additive affect of Q90L, Y107W and a polyhistidine tag was assessed and revealed that the major determinant in protein stability and prevention of amorphous and β-sheet specific aggregation is the quaternary structure. This study demonstrates that the destabilisation of the quaternary structure of DHDPS can result in the formation of amyloid-like aggregates by an (α/β)8 barrel, the first example of an (α/β)8 barrel misfolding in such a way. This finding supports the assertion that all proteins can form amyloid fibrils.

Demand forecasting performance is subject to the uncertainty underlying the time series an organisation is dealing with. There are many approaches that may be used to reduce demand uncertainty and consequently improve the forecasting (and inventory control) performance. An intuitively appealing such approach that is known to be effective is demand aggregation. One approach is to aggregate demand in lower-frequency 'time buckets'. Such an approach is often referred to, in the academic literature, as temporal aggregation. Another approach discussed in the literature is that associated with cross-sectional aggregation, which involves aggregating different time series to obtain higher level forecasts.This research discusses whether it is appropriate to use the original (not aggregated) data to generate a forecast or one should rather aggregate data first and then generate a forecast. This Ph.D. thesis reveals the conditions under which each approach leads to a superior performance as judged based on forecast accuracy. Throughout this work, it is assumed that the underlying structure of the demand time series follows an AutoRegressive Integrated Moving Average (ARIMA) process.In the first part of our1 research, the effect of temporal aggregation on demand forecasting is analysed. It is assumed that the non-aggregate demand follows an autoregressive moving average process of order one, ARMA(1,1). Additionally, the associated special cases of a first-order autoregressive process, AR(1) and a moving average process of order one, MA(1) are also considered, and a Single Exponential Smoothing (SES) procedure is used to forecast demand. These demand processes are often encountered in practice and SES is one of the standard estimators used in industry. Theoretical Mean Squared Error expressions are derived for the aggregate and the non-aggregate demand in order to contrast the relevant forecasting performances. The theoretical analysis is validated by an extensive numerical investigation and experimentation with an empirical dataset. The results indicate that performance improvements achieved through the aggregation approach are a function of the aggregation level, the smoothing constant value used for SES and the process parameters.In the second part of our research, the effect of cross-sectional aggregation on demand forecasting is evaluated. More specifically, the relative effectiveness of top-down (TD) and bottom-up (BU) approaches are compared for forecasting the aggregate and sub-aggregate demands. It is assumed that that the sub-aggregate demand follows either a ARMA(1,1) or a non-stationary Integrated Moving Average process of order one, IMA(1,1) and a SES procedure is used to extrapolate future requirements. Such demand processes are often encountered in practice and, as discussed above, SES is one of the standard estimators used in industry (in addition to being the optimal estimator for an IMA(1) process). Theoretical Mean Squared Errors are derived for the BU and TD approach in order to contrast the relevant forecasting performances. The theoretical analysis is supported by an extensive numerical investigation at both the aggregate and sub-aggregate levels in addition to empirically validating our findings on a real dataset from a European superstore. The results show that the superiority of each approach is a function of the series autocorrelation, the cross-correlation between series and the comparison level.Finally, for both parts of the research, valuable insights are offered to practitioners and an agenda for further research in this area is provided.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 1985.<br>MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE.<br>Vita.<br>Includes bibliographical references.<br>by Mark Stander Bowen.<br>Ph.D.

Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 114-124).<br>Protein aggregation underlies a number of human diseases. Most notably, it occurs widely in neurodegenerative diseases, including Alzheimer's and Parkinson's. At the molecular level, neurotoxicity is thought to originate from toxic gains of function in multimeric aggregates of proteins that are otherwise predominantly monomeric and disordered, fluctuating between a very large number of structurally dissimilar states on nano- and microsecond timescales. These proteins, termed Intrinsically Disordered Proteins (IDPs), are notoriously difficult to probe using traditional biophysical techniques. In order to obtain structural information pertaining to the aggregation of IDPs, it is often necessary to develop computational and modeling tools, both to leverage the full extent of the experimental data, and to generate testable predictions for future experiments. In this thesis, I present three separate computational studies studying the formation of multimeric aggregates in IDPs, spanning different aspects of the aggregation process, from early nucleation events to fibril elongation. In the first study, I present a conformational ensemble of a-synuclein, the culprit protein of Parkinson's disease, constructed using a Variational Bayesian Weighting algorithm in combination with NMR data collected by our collaborators. We find that the data fit a description in which the protein predominantly exists as a disordered monomer but contains small quantities of multimeric states containing both helical and strand-rich conformations. In the second study, I focus on the process of amyloid fibril elongation in the Amyloid-[beta] (A[beta]) peptide of Alzheimer's disease. I compute the free energy surface associated with the fibril elongation reaction, and find that elongation of both A[beta]40 and A[beta]42 experimental fibril structures occurs on a downhill free energy pathway, proceeding via an obligate, fibril-associated hairpin intermediate. The fibril-associated hairpin is significantly more stable (relative to the fibrillar, elongated state) in A[beta]42 compared with A[beta]40, suggesting a potential clinical target of interest. Finally, I present lengthy, all-atom molecular simulations that suggest that nucleation of the minimum aggregating fragment of c-synuclein proceeds via a helical intermediate, requiring a structural conversion into a strand-rich nucleating species via a stochastic process of individual helices unfolding and self-associating via backbone hydrogen bonds.<br>by Thomas Gurry.<br>Ph. D.

Streaming analytics deploy Kleene pattern queries to detect and aggregate event trends against high-rate data streams. Despite increasing workloads, most state-of-the-art systems process each query independently, thus missing cost-saving sharing opportunities. Sharing complex event trend aggregation poses several technical challenges. First, the execution of nested and diverse Kleene patterns is difficult to share. Second, we must share aggregate computation without the exponential costs of constructing the event trends. Third, not all sharing opportunities are beneficial because sharing aggregation introduces overhead. We propose a novel framework, Muse (Multi-query Snapshot Execution), that shares aggregation queries with Kleene patterns while avoiding expensive trend construction. It adopts an online sharing strategy that eliminates re-computations for shared sub-patterns. To determine the beneficial sharing plan, we introduce a cost model to estimate the sharing benefit and design the Muse refinement algorithm to efficiently select robust sharing candidates from the search space. Finally, we explore optimization decisions to further improve performance. Our experiments over a wide range of scenarios demonstrate that Muse increases throughput by 4 orders of magnitude compared to state-of-the-art approaches with negligible memory requirements.

An aggregation model which allows specification of primary particle size, density, and fractal dimension for two different particle types was written. Three stickiness values are used, the stickiness of each particle type to itself and the stickiness between particle types. Aggregation mechanisms considered include differential settling and turbulent shear. The model is used in three forms. In its simplest form, it operates on a closed system with aggregates breaking up when their size approaches the Kolmogorov scale. If the system begins with two types of primary particles, larger aggregates have uniform composition. A second version of the model includes removal of aggregates by settling. In this mode, the stickiness parameters dominate aggregate characteristics. Stickiness between similar particles controls the ratio of the particle type, whereas interparticle stickiness controls the particle removal rate. In the third form, three aggregation models are connected by a Rouse type suspended sediment model. This version models aggregate dynamics in the water column. Comparison of model results with total suspended sediment data and particulate organic carbon data from a site near the Poquoson River suggests that organic and inorganic constituents of suspended sediment do not stick together well. The dissertation also describes a new type of aggregation device called the rotating oscillating grid turbulent aggregation chamber (ROGTAC). This device combines the advantages of two types of aggregation devices which are commonly used, the oscillating grid device and the rolling cylinder device. Oscillating grid turbulence generators are preferred for creating uniform isotropic turbulence. However, when particles more dense than the fluid are placed in them, the particles settle out. Rotating cylinder devices are effective at keeping particles in suspension. They do this by keeping the fluid in them in solid body rotation, but in this mode the fluid is not experiencing shear. ROGTAC places an oscillating grid in one end of a rotating cylinder. The hydrodynamic characteristics were investigated using laser Doppler velocimetry. Turbulent energy dissipation rates calculated from LDV data agreed well with energy input calculated by applying the quadratic drag law to the grid.

Protein conformational diseases (PCD) include a range of degenerative disorders in which specific peptides or proteins misfold and aberrantly self-assemble, eventually forming amyloid-like fibrils, which constitute the hallmark of many neurodegenerative diseases. Plenty of works demonstrated that amyloid aggregation is strongly influenced by several extrinsic factors, such as high concentrations of macromolecules or the presence of proteases and chaperons. Molecular chaperones have been recognised as key players in the avoidance of amyloid fibril formation and, in particular, recent evidences demonstrate that low levels of chaperone heat-shock protein 70 kDa (Hsp70) are strictly related to the formation of intra-neuronal inclusions associated with Parkinson‘s (PD) and polyglutamine (polyQ) diseases. Human Hsp70 is composed of two major functional domains connected by a conserved interdomain linker: the 44-kDa N-terminal nucleotide-binding domain (NBD), with ATPase activity, followed by the 30-kDa substrate-binding domain (SBD) that contains a C-terminal lid subdomain (LS). Using a battery of Hsp70 variants, including full-length Hsp70 and SBD truncated variants, we have been able to discover an interaction between the LS of SBD and the interdomain linker, which we propose could play an important role in the allosteric communication between NBD and SBD. Therefore, we analyzed the anti-amyloidogenic activity of Hsp70, using two model proteins: alpha-synuclein (AS), whose deposition in the brain is associated with PD and the polyQ protein ataxin-3 (AT3), the causative agent of the Machado-Joseph disease (MCD). We demonstrated Hsp70 is able to interact and stabilize pre-fibrillar species formed during amyloid aggregation and that the binding mechanism of these species is different from that of the monomeric protein. Plenty of evidence supports the idea that protein aggregation observed in in vitro experimental conditions is different from that naturally occurring in in vivo systems. This is also related with the fact that the high concentration of macromolecules present in the intra- and extra-cellular compartments, a condition known as molecular crowding (MC), strongly affects protein folding and aggregation. Here, we successfully employed Escherichia coli as in vivo model for studying the aggregation mechanism of the polyQ protein ataxin-3 (AT3) in the presence of MC. In particular we investigated the relationship between the aggregation pathway and cytotoxicity and we were able to characterize the kinetic of formation of aggregated toxic and non-toxic species of AT3. Our future efforts will be aimed to investigate in vivo Hsp70 action by analyzing structural and physiological features of AT3 aggregated species formed in the intracellular environment of E. coli that co-express Hsp70 under different conditions.

In this work we have studied, by means of Molecular Dynamics simulations, the process of denaturation and self-assembly of short oligonucleotides. Supramolecular ordering of DNA short strands is a promising field which is constantly enriched with new findings. Examples are provided by micellar and fibrils formations and due to the selectivity of DNA bindings, "intelligent" devices have been developed to perform simple logic operations. It is worth to notice that computer simulations of these DNA nanosystems would complement experiments with detailed insight into processes involved in self-assembly. In order to obtain an accurate description of the interactions involved in the complex structure of DNA we used oxDNA, a coarse-grained model developed by Ouldridge. We simulated the melting transition of 4, 6, and 8 base pair sequences. Sequence and length dependence were analyzed, specifically we compared thermodynamic parameters DeltaH, DeltaS and the melting temperature with literature results. Moreover, we have attempted to reproduce liquid crystal ordering of the ultrashort sequence GCCG at relatively high saline concentration, until now only experimentally observed in Bellini's works. We found that our simple model successfully reproduces the experimental phase sequence (isotropic, nematic, columnar) at T= 5 °C as a function of oligonucleotide concentration, and we fully characterized the microscopic structure of the three phases.

Aggregation of the Amyloid β (Aβ) peptide to amyloid fibrils is associated with the outbreak of Alzheimer’s disease. Early aggregation intermediates in form of soluble oligomers are of special interest as they are believed to be the major toxic components in the process. These oligomers are of disordered and transient nature. Therefore, their detailed molecular structure is difficult to access experimentally and often remains unknown. In the present work extensive, fully atomistic replica exchange molecular dynamics simulations were performed to study the preaggregated, monomer states and early aggregation intermediates (dimers, trimers) of Aβ(25-35) and Aβ(10-35)-NH2 in aqueous solution. The folding and aggregation of Aβ(25-35) were studied at neutral pH and 293 K. Aβ(25-35) monomers mainly adopt β-hairpin conformations characterized by a β-turn formed by residues G29 and A30, and a β-sheet between residues N27–K28 and I31–I32 in equilibrium with coiled conformations. The β-hairpin conformations served as initial configurations to model spontaneous aggregation of Aβ(25-35). As expected, within the Aβ(25-35) dimer and trimer ensembles many different poorly populated conformations appear. Nevertheless, we were able to distinguish between disordered and fibril-like oligomers. Whereas disordered oligomers are rather compact with few intermolecular hydrogen bonds (HBs), fibril-like oligomers are characterized by the formation of large intermolecular β-sheets. In most of the fibril-like dimers and trimers individual peptides are fully extended forming in- or out-of-register antiparallel β-sheets. A small amount of fibril-like trimers contained V-shaped peptides forming parallel β-sheets. The dimensions of extended and V-shaped oligomers correspond well to the diameters of two distinct morphologies found for Aβ(25-35) fibrils. The transition from disordered to fibril-like Aβ(25-35) dimers is unfavorable but driven by energy. The lower energy of fibril-like dimers arises from favorable intermolecular HBs and other electrostatic interactions which compete with a loss in entropy. Approximately 25 % of the entropic cost correspond to configurational entropy. The rest relates to solvent entropy, presumably caused by hydrophobic and electrostatic effects. In contrast to the transition towards fibril-like dimers the first step of aggregation is driven by entropy. Here, we compared structural and thermodynamic properties of the individual monomer, dimer and trimer ensembles to gain qualitative information about the aggregation process. The β-hairpin conformation observed for monomers is successively dissolved in dimer and trimer ensembles while instead intermolecular β-sheets are formed. As expected upon aggregation the configurational entropy decreases. Additionally, the solvent accessible surface area (SASA), especially the hydrophobic SASA, decreases yielding a favorable solvation free energy which overcompensates the loss in configurational entropy. In summary, the hydrophobic effect, possibly combined with electrostatic effects, yields an increase in solvent entropy which is believed to be one major driving force towards aggregation. Spontaneous folding of the Aβ(10-35)-NH2 monomer was modeled using two force fields, GROMOS96 43a1 and OPLS/AA, and compared to primary NMR data collected at pH 5.6 and 283 K taken from the literature. Unexpectedly, the two force fields yielded significantly different main conformations. Comparison between experimental and calculated nuclear Overhauser effect (NOE) distances is not sufficient to distinguish between the different force fields. Additionally, the comparison with scalar coupling constants suggest that the chosen protonation in both simulations corresponds to a pH lower than in the experiment. Based on this analysis we were unable to determine which force field yields a better description of this system. Dimerization of Aβ(10-35)-NH2 was studied at neutral pH and 300 K. Dimer conformations arrange in many distinct, poorly populated and rather complex alignments or interlocking patterns which are rather stabilized by side chain interactions than by specific intermolecular hydrogen bonds. Similar to Aβ(25-35) dimers, transition towards β-sheet-rich, fibril-like Aβ(10-35) dimers is driven by energy competing with a loss in entropy. Here, transition is mediated by favorable peptide-solvent and solvent-solvent interactions mainly arising from electrostatic interactions.<br>Die Aggregation des Amyloid β (Aβ) Peptids zu Amyloidfibrillen wird mit dem Ausbruch der Alzheimer Krankheit in Verbindung gebracht. Die toxische Wirkung auf Zellen wird vor allem den zeitigen Intermediaten in Form von löslichen Oligomeren zugeschrieben. Aufgrund deren ungeordneter und flüchtiger Natur kann die molekulare Struktur solcher zeitigen Oligomere oft experimentell nicht aufgelöst werden. In der vorliegenden Arbeit wurden aufwendige atomistische Replica-Exchange-Molekulardynamik-Simulationen durchgeführt, um die molekulare Struktur von Monomeren und Oligomeren der Fragmente Aβ(25-35) und Aβ(10-35)-NH2 in Wasser zu untersuchen. Die Faltung und Aggregation von Aβ(25-35) wurde bei neutralem pH und 293 K untersucht. Monomere dieses Fragments bilden hauptsächlich β-Haarnadelkonformationen im Gleichgewicht mit Knäulstrukturen. Innerhalb der β-Haarnadelkonformationen bilden die Residuen G29 und A30 einen β-turn, während N27–K28 and I31–I32 ein β-Faltblatt bilden. Diese β-Haarnadelkonformationen bildeten den Ausgangspunkt zur Modellierung spontaner Aggregation. Wie zu erwarten, bilden sich eine Vielzahl verschiedener, gering besetzter Dimer- und Trimerkonformationen. Mit Hilfe einer gröberen Einteilung können diese in ungeordnete und fibrillähnliche Oligomere unterteilt werden. Ungeordnete Oligomere bilden kompakte Strukturen, die nur durch wenige intermolekulare Wasserstoffbrückenbindungen (HBB) stabilisiert sind. Typisch für fibrillähnliche Oligomere ist hingegen die Ausbildung großer intermolekularer β-Faltblätter. In vielen dieser Oligomere finden wir antiparallele, in- oder out-of-register β-Faltblätter gebildet durch vollständig ausgestreckte Peptide. Ein kleiner Teil der fibrillähnlichen Trimere bildet parallele, V-förmige β-Faltblätter. Die Ausdehnungen ausgestreckter und V-förmiger Oligomere entspricht in etwa den Durchmessern von zwei verschiedenen, experimentell gefundenen Fibrillmorphologien für Aβ(25-35). Die Umwandlung von ungeordneten zu fibrillähnlichen Aβ(25-35) Dimeren ist energetisch begünstigt, läuft aber nicht freiwillig ab. Fibrillähnliche Dimere haben eine geringere Energie aufgrund günstiger Peptidwechselwirkungen (HBB, Salzbrücken), welche durch den Verlust an Entropie kompensiert wird. Etwa 25 % entsprechen dem Verlust an Konfigurationsentropie. Der restliche Anteil wird einem Verlust an Lösungsmittelentropie aufgrund von hydrophoben und elektrostatischen Effekten zugesprochen. Im Gegensatz zur Umwandlung in fibrillähnliche Dimere, ist die Assoziation von Monomeren oder Oligomeren entropisch begünstigt. Beim Vergleich thermodynamischer Eigenschaften der Monomer-, Dimer- und Trimersysteme zeigt sich im Verlauf der Aggregation, wie erwartet, eine Abnahme der Konfigurationsentropie. Zusätzlich nimmt die dem Lösungsmittel zugängliche Oberfläche (SASA), insbesondere die hydrophobe SASA, ab. In Verbindung damit beobachten wir eine Abnahme der freien Solvatisierungsenergie, welche den Verlust an Konfigurationsentropie kompensiert. Mit anderen Worten, der hydrophobe Effekt in Kombination mit elektrostatischen Wechselwirkungen führt zu einem Ansteigen der Lösungsmittelentropie und begünstigt damit die Aggegation. Die spontane Faltung des Aβ(10-35)-NH2 Monomers wurde für zwei verschiedene Proteinkraftfelder, GROMOS96 43a1 und OPLS/AA, untersucht und mit primären NMR-Daten aus der Literatur, gemessen bei pH 5.6 und 283 K, verglichen. Beide Kraftfelder generieren unterschiedliche Hauptkonformationen. Der Vergleich zwischen experimentellen und berechneten Kern-Overhauser-Effekt (NOE) Abständen ist nicht ausreichend, um zwischen beiden Kraftfeldern zu unterscheiden. Der Vergleich mit Kopplungskonstanten aus Experiment und Simulation zeigt, dass beide Simulationen einem pH-Wert geringer als 5.6 ensprechen. Basierend auf den bisherigen Ergebnissen können wir nicht entscheiden, welches Kraftfeld eine bessere Beschreibung für dieses System liefert. Die Dimerisierung von Aβ(10-35)-NH2 wurde bei neutralem pH und 300 K untersucht. Wir finden eine Vielzahl verschiedener, gering besetzter Dimerstrukturen, welche eher durch Seitenkettenkontakte als durch spezifische HBB stabilisiert sind. Wie bei den Aβ(25-35) Dimeren, ist die Umwandlung zu β-Faltblattreichen, fibrillähnlichen Aβ(10-35) Dimeren energetisch begünstigt, konkurriert aber mit einem Entropieverlust. Die Umwandlung wird in diesem Fall durch elektrostatische Wechselwirkungen zwischen Peptid und Lösungsmittel und innerhalb des Lösungsmittels bestimmt.

Hardware has physical limitations. It has fixed performance limits, and may fail. Applications suffer from the limitations of the physical hardware on which they run. Making applications able to take advantage of multiple hardware instances to avoid these limitations is complex. Since this effort must be expended for every application, it is impractical for most of them. In this thesis, we show that we can aggregate multiple physical machines at the virtual machine interface, allowing them to transcend the limitations of single machines without changing the applications themselves.<br>Science, Faculty of<br>Computer Science, Department of<br>Graduate