968 resultados para Multi-cluster


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If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm 'unique' solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for 'truly' typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted. (C) 2003 Elsevier Science Ltd. All rights reserved.

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Based on the idea of an important cluster, a new multi-level probabilistic neural network (MLPNN) is introduced. The MLPNN uses an incremental constructive approach, i.e. it grows level by level. The construction algorithm of the MLPNN is proposed such that the classification accuracy monotonically increases to ensure that the classification accuracy of the MLPNN is higher than or equal to that of the traditional PNN. Numerical examples are included to demonstrate the effectiveness of proposed new approach.

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Recent research in multi-agent systems incorporate fault tolerance concepts. However, the research does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely ‘Intelligent Agents’. In the approach considered a task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The agents hence contribute towards fault tolerance and towards building reliable systems. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

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The fungal family Clavicipitaceae includes plant symbionts and parasites that produce several psychoactive and bioprotective alkaloids. The family includes grass symbionts in the epichloae clade (Epichloë and Neotyphodium species), which are extraordinarily diverse both in their host interactions and in their alkaloid profiles. Epichloae produce alkaloids of four distinct classes, all of which deter insects, and some—including the infamous ergot alkaloids—have potent effects on mammals. The exceptional chemotypic diversity of the epichloae may relate to their broad range of host interactions, whereby some are pathogenic and contagious, others are mutualistic and vertically transmitted (seed-borne), and still others vary in pathogenic or mutualistic behavior. We profiled the alkaloids and sequenced the genomes of 10 epichloae, three ergot fungi (Claviceps species), a morning-glory symbiont (Periglandula ipomoeae), and a bamboo pathogen (Aciculosporium take), and compared the gene clusters for four classes of alkaloids. Results indicated a strong tendency for alkaloid loci to have conserved cores that specify the skeleton structures and peripheral genes that determine chemical variations that are known to affect their pharmacological specificities. Generally, gene locations in cluster peripheries positioned them near to transposon-derived, AT-rich repeat blocks, which were probably involved in gene losses, duplications, and neofunctionalizations. The alkaloid loci in the epichloae had unusual structures riddled with large, complex, and dynamic repeat blocks. This feature was not reflective of overall differences in repeat contents in the genomes, nor was it characteristic of most other specialized metabolism loci. The organization and dynamics of alkaloid loci and abundant repeat blocks in the epichloae suggested that these fungi are under selection for alkaloid diversification. We suggest that such selection is related to the variable life histories of the epichloae, their protective roles as symbionts, and their associations with the highly speciose and ecologically diverse cool-season grasses.

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Boreal winter wind storm situations over Central Europe are investigated by means of an objective cluster analysis. Surface data from the NCEP-Reanalysis and ECHAM4/OPYC3-climate change GHG simulation (IS92a) are considered. To achieve an optimum separation of clusters of extreme storm conditions, 55 clusters of weather patterns are differentiated. To reduce the computational effort, a PCA is initially performed, leading to a data reduction of about 98 %. The clustering itself was computed on 3-day periods constructed with the first six PCs using "k-means" clustering algorithm. The applied method enables an evaluation of the time evolution of the synoptic developments. The climate change signal is constructed by a projection of the GCM simulation on the EOFs attained from the NCEP-Reanalysis. Consequently, the same clusters are obtained and frequency distributions can be compared. For Central Europe, four primary storm clusters are identified. These clusters feature almost 72 % of the historical extreme storms events and add only to 5 % of the total relative frequency. Moreover, they show a statistically significant signature in the associated wind fields over Europe. An increased frequency of Central European storm clusters is detected with enhanced GHG conditions, associated with an enhancement of the pressure gradient over Central Europe. Consequently, more intense wind events over Central Europe are expected. The presented algorithm will be highly valuable for the analysis of huge data amounts as is required for e.g. multi-model ensemble analysis, particularly because of the enormous data reduction.

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ESA’s first multi-satellite mission Cluster is unique in its concept of 4 satellites orbiting in controlled formations. This will give an unprecedented opportunity to study structure and dynamics of the magnetosphere. In this paper we discuss ways in which ground-based remote-sensing observations of the ionosphere can be used to support the multipoint in-situ satellite measurements. There are a very large number of potentially useful configurations between the satellites and any one ground-based observatory; however, the number of ideal occurrences for any one configuration is low. Many of the ground-based instruments cannot operate continuously and Cluster will take data only for a part of each orbit, depending on how much high-resolution (‘burst-mode’) data are acquired. In addition, there are a great many instrument modes and the formation, size and shape of the cluster of the four satellites to consider. These circumstances create a clear and pressing need for careful planning to ensure that the scientific return from Cluster is maximised by additional coordinated ground-based observations. For this reason, ESA established a working group to coordinate the observations on the ground with Cluster. We will give a number of examples how the combined spacecraft and ground-based observations can address outstanding questions in magnetospheric physics. An online computer tool has been prepared to allow for the planning of conjunctions and advantageous constellations between the Cluster spacecraft and individual or combined ground-based systems. During the mission a ground-based database containing index and summary data will help to identify interesting datasets and allow to select intervals for coordinated studies. We illustrate the philosophy of our approach, using a few important examples of the many possible configurations between the satellite and the ground-based instruments.

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The environment where galaxies are found heavily influences their evolution. Close groupings, like the ones in the cores of galaxy clusters or compact groups, evolve in ways far more dramatic than their isolated counterparts. We have conducted a multi-wavelength study of Hickson Compact Group 7 (HCG 7), consisting of four giant galaxies: three spirals and one lenticular. We use Hubble Space Telescope (HST) imaging to identify and characterize the young and old star cluster populations. We find young massive clusters (YMCs) mostly in the three spirals, while the lenticular features a large, unimodal population of globular clusters (GCs) but no detectable clusters with ages less than a few Gyr. The spatial and approximate age distributions of the similar to 300 YMCs and similar to 150 GCs thus hint at a regular star formation history in the group over a Hubble time. While at first glance the HST data show the galaxies as undisturbed, our deep ground-based, wide-field imaging that extends the HST coverage reveals faint signatures of stellar material in the intragroup medium (IGM). We do not, however, detect the IGM in H I or Chandra X-ray observations, signatures that would be expected to arise from major mergers. Despite this fact, we find that the H I gas content of the individual galaxies and the group as a whole are a third of the expected abundance. The appearance of quiescence is challenged by spectroscopy that reveals an intense ionization continuum in one galaxy nucleus, and post-burst characteristics in another. Our spectroscopic survey of dwarf galaxy members yields a single dwarf elliptical galaxy in an apparent stellar tidal feature. Based on all this information, we suggest an evolutionary scenario for HCG 7, whereby the galaxies convert most of their available gas into stars without the influence of major mergers and ultimately result in a dry merger. As the conditions governing compact groups are reminiscent of galaxies at intermediate redshift, we propose that HCGs are appropriate for studying galaxy evolution at z similar to 1-2.

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In this paper, we present an algorithm for cluster analysis that integrates aspects from cluster ensemble and multi-objective clustering. The algorithm is based on a Pareto-based multi-objective genetic algorithm, with a special crossover operator, which uses clustering validation measures as objective functions. The algorithm proposed can deal with data sets presenting different types of clusters, without the need of expertise in cluster analysis. its result is a concise set of partitions representing alternative trade-offs among the objective functions. We compare the results obtained with our algorithm, in the context of gene expression data sets, to those achieved with multi-objective Clustering with automatic K-determination (MOCK). the algorithm most closely related to ours. (C) 2009 Elsevier B.V. All rights reserved.

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Predictors of random effects are usually based on the popular mixed effects (ME) model developed under the assumption that the sample is obtained from a conceptual infinite population; such predictors are employed even when the actual population is finite. Two alternatives that incorporate the finite nature of the population are obtained from the superpopulation model proposed by Scott and Smith (1969. Estimation in multi-stage surveys. J. Amer. Statist. Assoc. 64, 830-840) or from the finite population mixed model recently proposed by Stanek and Singer (2004. Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 1119-1130). Predictors derived under the latter model with the additional assumptions that all variance components are known and that within-cluster variances are equal have smaller mean squared error (MSE) than the competitors based on either the ME or Scott and Smith`s models. As population variances are rarely known, we propose method of moment estimators to obtain empirical predictors and conduct a simulation study to evaluate their performance. The results suggest that the finite population mixed model empirical predictor is more stable than its competitors since, in terms of MSE, it is either the best or the second best and when second best, its performance lies within acceptable limits. When both cluster and unit intra-class correlation coefficients are very high (e.g., 0.95 or more), the performance of the empirical predictors derived under the three models is similar. (c) 2007 Elsevier B.V. All rights reserved.

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The Cladocera assemblages in two cascade reservoirs located in the Paranapanema River in Brazil were studied during two consecutive years. Upstream Chavantes Reservoir is an accumulation system, with a long water retention time, high depth and oligo-mesotrophic status. The downstream Salto Grande Reservoir is a small, run-of-river reservoir, with a short water retention time, shallow depth and meso-eutrophic status. The goal of this study was to determine the inter- and intra-reservoir limnological differences with emphasis on the Cladocerans assemblages. The following questions were posed: (i) what are the seasonal dynamics of the reservoir spatial structures; (ii) how dynamics, seasonally, is the reservoirs spatial structure; and (iii) are the reservoir independent systems? A total of 43 Cladoceran species were identified in this study. Ceriodaphnia silvestrii was the most abundant and frequent species found in Chavantes Reservoir, while C. cornuta was most abundant and frequent in Salto Grande Reservoir. The Cladoceran species richness differed significantly among sampling sites for both reservoirs. In terms of abundance, there was a significant variation among sampling sites and periods for both reservoirs. A cluster analysis indicated a higher similarity among the deeper compartments, and the intermediate river-reservoir zones was grouped with the riverine sampling sites. For the smaller Salto Grande Reservoir, the entrance of a middle size tributary causes major changes in the system. A distinct environment was observed in the river mouth zone of another small tributary, representing a shallow environment with aquatic macrophyte stands. A canonical correlation analysis between environmental variables and Cladoceran abundance explained 75% of the data variability, and a complementary factorial analysis explained 65% of the variability. The spatial compartmentalization of the reservoirs, as well as the particular characteristics of the two study reservoirs, directly influenced the structure of the Cladoceran assemblages. The conditions of the lacustrine (dam) zone of the larger Chavantes Reservoir were reflected in the upstream zone of the smaller downstream Salto Grande Reservoir, highlighting the importance of plankton exportation in reservoir cascade systems. The comparative spatial-temporal analysis indicated conspicuous differences between the two reservoirs, reinforcing the necessity of considering tropical/subtropical reservoirs as complex, multi-compartmental water systems. © 2010 The Authors. Journal compilation © 2010 Blackwell Publishing Asia Pty Ltd.

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This paper presents the development of an multi-projection stereoscopic dental arches application with semantic descriptions. The first section presents the concepts of the used technologies. Applications and examples are demonstrated. Finally, is presented the physical structure and the developed system, where a 3D dental arch is used as a model and can be viewed in multi-projection, thereby, providing greater user's immersion. ©2010 IEEE.

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Unlike traditional wireless networks, characterized by the presence of last-mile, static and reliable infrastructures, Mobile ad Hoc Networks (MANETs) are dynamically formed by collections of mobile and static terminals that exchange data by enabling each other's communication. Supporting multi-hop communication in a MANET is a challenging research area because it requires cooperation between different protocol layers (MAC, routing, transport). In particular, MAC and routing protocols could be considered mutually cooperative protocol layers. When a route is established, the exposed and hidden terminal problems at MAC layer may decrease the end-to-end performance proportionally with the length of each route. Conversely, the contention at MAC layer may cause a routing protocol to respond by initiating new routes queries and routing table updates. Multi-hop communication may also benefit the presence of pseudo-centralized virtual infrastructures obtained by grouping nodes into clusters. Clustering structures may facilitate the spatial reuse of resources by increasing the system capacity: at the same time, the clustering hierarchy may be used to coordinate transmissions events inside the network and to support intra-cluster routing schemes. Again, MAC and clustering protocols could be considered mutually cooperative protocol layers: the clustering scheme could support MAC layer coordination among nodes, by shifting the distributed MAC paradigm towards a pseudo-centralized MAC paradigm. On the other hand, the system benefits of the clustering scheme could be emphasized by the pseudo-centralized MAC layer with the support for differentiated access priorities and controlled contention. In this thesis, we propose cross-layer solutions involving joint design of MAC, clustering and routing protocols in MANETs. As main contribution, we study and analyze the integration of MAC and clustering schemes to support multi-hop communication in large-scale ad hoc networks. A novel clustering protocol, named Availability Clustering (AC), is defined under general nodes' heterogeneity assumptions in terms of connectivity, available energy and relative mobility. On this basis, we design and analyze a distributed and adaptive MAC protocol, named Differentiated Distributed Coordination Function (DDCF), whose focus is to implement adaptive access differentiation based on the node roles, which have been assigned by the upper-layer's clustering scheme. We extensively simulate the proposed clustering scheme by showing its effectiveness in dominating the network dynamics, under some stressing mobility models and different mobility rates. Based on these results, we propose a possible application of the cross-layer MAC+Clustering scheme to support the fast propagation of alert messages in a vehicular environment. At the same time, we investigate the integration of MAC and routing protocols in large scale multi-hop ad-hoc networks. A novel multipath routing scheme is proposed, by extending the AOMDV protocol with a novel load-balancing approach to concurrently distribute the traffic among the multiple paths. We also study the composition effect of a IEEE 802.11-based enhanced MAC forwarding mechanism called Fast Forward (FF), used to reduce the effects of self-contention among frames at the MAC layer. The protocol framework is modelled and extensively simulated for a large set of metrics and scenarios. For both the schemes, the simulation results reveal the benefits of the cross-layer MAC+routing and MAC+clustering approaches over single-layer solutions.

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During the last years we assisted to an exponential growth of scientific discoveries for catalysis by gold and many applications have been found for Au-based catalysts. In the literature there are several studies concerning the use of gold-based catalysts for environmental applications and good results are reported for the catalytic combustion of different volatile organic compounds (VOCs). Recently it has also been established that gold-based catalysts are potentially capable of being effectively employed in fuel cells in order to remove CO traces by preferential CO oxidation in H2-rich streams. Bi-metallic catalysts have attracted increasing attention because of their markedly different properties from either of the costituent metals, and above all their enhanced catalytic activity, selectivity and stability. In the literature there are several studies demostrating the beneficial effect due to the addition of an iron component to gold supported catalysts in terms of enhanced activity, selectivity, resistence to deactivation and prolonged lifetime of the catalyst. In this work we tried to develop a methodology for the preparation of iron stabilized gold nanoparticles with controlled size and composition, particularly in terms of obtaining an intimate contact between different phases, since it is well known that the catalytic behaviour of multi-component supported catalysts is strongly influenced by the size of the metal particles and by their reciprocal interaction. Ligand stabilized metal clusters, with nanometric dimensions, are possible precursors for the preparation of catalytically active nanoparticles with controlled dimensions and compositions. Among these, metal carbonyl clusters are quite attractive, since they can be prepared with several different sizes and compositions and, moreover, they are decomposed under very mild conditions. A novel preparation method was developed during this thesis for the preparation of iron and gold/iron supported catalysts using bi-metallic carbonyl clusters as precursors of highly dispersed nanoparticles over TiO2 and CeO2, which are widely considered two of the most suitable supports for gold nanoparticles. Au/FeOx catalysts were prepared by employing the bi-metallic carbonyl cluster salts [NEt4]4[Au4Fe4(CO)16] (Fe/Au=1) and [NEt4][AuFe4(CO)16] (Fe/Au=4), and for comparison FeOx samples were prepared by employing the homometallic [NEt4][HFe3(CO)11] cluster. These clusters were prepared by Prof. Longoni research group (Department of Physical and Inorganic Chemistry- University of Bologna). Particular attention was dedicated to the optimization of a suitable thermal treatment in order to achieve, apart from a good Au and Fe metal dispersion, also the formation of appropriate species with good catalytic properties. A deep IR study was carried out in order to understand the physical interaction between clusters and different supports and detect the occurrence of chemical reactions between them at any stage of the preparation. The characterization by BET, XRD, TEM, H2-TPR, ICP-AES and XPS was performed in order to investigate the catalysts properties, whit particular attention to the interaction between Au and Fe and its influence on the catalytic activity. This novel preparation method resulted in small gold metallic nanoparticles surrounded by highly dispersed iron oxide species, essentially in an amorphous phase, on both TiO2 and CeO2. The results presented in this thesis confirmed that FeOx species can stabilize small Au particles, since keeping costant the gold content but introducing a higher iron amount a higher metal dispersion was achieved. Partial encapsulation of gold atoms by iron species was observed since the Au/Fe surface ratio was found much lower than bulk ratio and a strong interaction between gold and oxide species, both of iron oxide and supports, was achieved. The prepared catalysts were tested in the total oxidation of VOCs, using toluene and methanol as probe molecules for aromatics and alchols, respectively, and in the PROX reaction. Different performances were observed on titania and ceria catalysts, on both toluene and methanol combustion. Toluene combustion on titania catalyst was found to be enhanced increasing iron loading while a moderate effect on FeOx-Ti activity was achieved by Au addition. In this case toluene combustion was improved due to a higher oxygen mobility depending on enhanced oxygen activation by FeOx and Au/FeOx dispersed on titania. On the contrary ceria activity was strongly decreased in the presence of FeOx, while the introduction of gold was found to moderate the detrimental effect of iron species. In fact, excellent ceria performances are due to its ability to adsorb toluene and O2. Since toluene activation is the determining factor for its oxidation, the partial coverage of ceria sites, responsible of toluene adsorption, by FeOx species finely dispersed on the surface resulted in worse efficiency in toluene combustion. Better results were obtained for both ceria and titania catalysts on methanol total oxidation. In this case, the performances achieved on differently supported catalysts indicate that the oxygen mobility is the determining factor in this reaction. The introduction of gold on both TiO2 and CeO2 catalysts, lead to a higher oxygen mobility due to the weakening of both Fe-O and Ce-O bonds and consequently to enhanced methanol combustion. The catalytic activity was found to strongly depend on oxygen mobility and followed the same trend observed for catalysts reducibility. Regarding CO PROX reaction, it was observed that Au/FeOx titania catalysts are less active than ceria ones, due to the lower reducibility of titania compared to ceria. In fact the availability of lattice oxygen involved in PROX reaction is much higher in the latter catalysts. However, the CO PROX performances observed for ceria catalysts are not really high compared to data reported in literature, probably due to the very low Au/Fe surface ratio achieved with this preparation method. CO preferential oxidation was found to strongly depend on Au particle size but also on surface oxygen reducibility, depending on the different oxide species which can be formed using different thermal treatment conditions or varying the iron loading over the support.

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Gli ammassi globulari rappresentano i laboratori ideali nei quali studiare la dinamica di sistemi ad N-corpi ed i suoi effetti sull’evoluzione stellare. Infatti, gli ammassi globulari sono gli unici sistemi astrofisici che, entro il tempo scala dell’età dell’Universo, sperimentano quasi tutti i processi di dinamica stellare noti. Questo lavoro di tesi si inserisce in un progetto a lungo termine volto a fornire una dettagliata caratterizzazione delle proprietà dinamiche degli ammassi globulari galattici. In questa ricerca, strumenti di fondamentale importanza sono il profilo di dispersione di velocità del sistema e la sua curva di rotazione. Per determinare le componenti radiali di questi profili cinematici in ammassi globulari galattici è necessario misurare la velocità lungo la linea di vista di un ampio campione di stelle membre, a differenti distanze dal centro. Seguendo un approccio multi-strumentale, è possibile campionare l’intera estensione radiale dell’ammasso utilizzando spettrografi multi-oggetto ad alta risoluzione spettrale nelle regioni intermedie/esterne, e spettrografi IFU con ottiche adattive per le regioni centrali (pochi secondi d’arco dal centro). Questo lavoro di tesi è volto a determinare il profilo di dispersione di velocità dell’ammasso globulare 47 Tucanae, campionando un’estensione radiale compresa tra circa 20'' e 13' dal centro. Per questo scopo sono state misurate le velocità radiali di circa un migliaio di stelle nella direzione di 47 Tucanae, utilizzando spettri ad alta risoluzione ottenuti con lo spettrografo multi-oggetto FLAMES montato al Very Large Telescope dell’ESO. Le velocità radiali sono state misurate utilizzando la tecnica di cross-correlazione tra gli spettri osservati e appropriati spettri teorici, e sono state ottenute accuratezze inferiori a 0.5km/s. Il campione così ottenuto (complementare a quello raccolto con strumenti IFU nelle regioni centrali) è fondamentale per costruire il profilo di dispersione di velocità dell’ammasso e la sua eventuale curva di rotazione. Questi dati, combinati col profilo di densità dell’ammasso precedentemente determinato, permetteranno di vincolare opportunamente modelli teorici come quelli di King (1966) o di Wilson (1975), e di arrivare così alla prima solida determinazione dei parametri strutturali e dinamici (raggi di core e di metà massa, tempo di rilassamento, parametro collisionale, etc.) e della massa totale e distribuzione di massa del sistema.

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Multi-parametric and quantitative magnetic resonance imaging (MRI) techniques have come into the focus of interest, both as a research and diagnostic modality for the evaluation of patients suffering from mild cognitive decline and overt dementia. In this study we address the question, if disease related quantitative magnetization transfer effects (qMT) within the intra- and extracellular matrices of the hippocampus may aid in the differentiation between clinically diagnosed patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI) and healthy controls. We evaluated 22 patients with AD (n=12) and MCI (n=10) and 22 healthy elderly (n=12) and younger (n=10) controls with multi-parametric MRI. Neuropsychological testing was performed in patients and elderly controls (n=34). In order to quantify the qMT effects, the absorption spectrum was sampled at relevant off-resonance frequencies. The qMT-parameters were calculated according to a two-pool spin-bath model including the T1- and T2 relaxation parameters of the free pool, determined in separate experiments. Histograms (fixed bin-size) of the normalized qMT-parameter values (z-scores) within the anterior and posterior hippocampus (hippocampal head and body) were subjected to a fuzzy-c-means classification algorithm with downstreamed PCA projection. The within-cluster sums of point-to-centroid distances were used to examine the effects of qMT- and diffusion anisotropy parameters on the discrimination of healthy volunteers, patients with Alzheimer and MCIs. The qMT-parameters T2(r) (T2 of the restricted pool) and F (fractional pool size) differentiated between the three groups (control, MCI and AD) in the anterior hippocampus. In our cohort, the MT ratio, as proposed in previous reports, did not differentiate between MCI and AD or healthy controls and MCI, but between healthy controls and AD.