Reconstruction of networks from their betweenness centrality

In this paper we study the reconstruction of a network topology from the values of its betweenness centrality, a measure of the influence of each of its nodes in the dissemination of information over the network. We consider a simple metaheuristic, simulated annealing, as the combinatorial optimization method to generate the network from the values of the betweenness centrality. We compare the performance of this technique when reconstructing different categories of networks –random, regular, small-world, scale-free and clustered–. We show that the method allows an exact reconstruction of small networks and leads to good topological approximations in the case of networks with larger orders. The method can be used to generate a quasi-optimal topology fora communication network from a list with the values of the maximum allowable traffic for each node.

Joint physical-MAC layer design of the broadcast channel protocol in adhoc networks

Broadcast transmission mode in ad hoc networks is critical to manage multihop routing or providing medium accesscontrol (MAC)-layer fairness. In this paper, it is shown that ahigher capacity to exchange information among neighbors may beobtained through a physical-MAC cross-layer design of the broadcastprotocol exploiting signal separation principles. Coherentdetection and separation of contending nodes is possible throughtraining sequences which are selected at random from a reducedset. Guidelines for the design of this set are derived for a lowimpact on the network performance and the receiver complexity.

Input diffusion and the evolution of production networks

What determines which inputs are initially considered and eventually adopted in the productionof new or improved goods? Why are some inputs much more prominent than others? We modelthe evolution of input linkages as a process where new producers first search for potentially usefulinputs and then decide which ones to adopt. A new product initially draws a set of 'essentialsuppliers'. The search stage is then confined to the network neighborhood of the latter, i.e., to theinputs used by the essential suppliers. The adoption decision is driven by a tradeoff between thebenefits accruing from input variety and the costs of input adoption. This has important implicationsfor the number of forward linkages that a product (input variety) develops over time. Inputdiffusion is fostered by network centrality ? an input that is initially represented in many networkneighborhoods is subsequently more likely to be adopted. This mechanism also delivers a powerlaw distribution of forward linkages. Our predictions continue to hold when varieties are aggregatedinto sectors. We can thus test them, using detailed sectoral US input-output tables. We showthat initial network proximity of a sector in 1967 significantly increases the likelihood of adoptionthroughout the subsequent four decades. The same is true for rapid productivity growth in aninput-producing sector. Our empirical results highlight two conditions for new products to becomecentral nodes: initial network proximity to prospective adopters, and technological progress thatreduces their relative price. Semiconductors met both conditions.

Separation mechanisms in nanofiltration and retention changes of organic compounds

Orgaanisten yhdisteiden negatiivinen retentio nanosuodatuksessa on ilmiö, jota eiole kovin paljon tutkittu. Negatiivisen retentioon vaikuttavat syyt tai tekijäteivät ole kovin hyvin tiedossa. Erotusmenetelmänä negatiivinen retentio voi olla käyttökelpoinen tietyissä sovelluksissa. Työn kirjallisuusosa käsittelee nanosuodatuksen erotusmekanismeja ja retentioon vaikuttavia tekijöitä. Myös joitakin malleja on esitetty. Nanosuodatus on monimutkainen prosessi, josta ei voida löytää vain yhtä erotusmekanismia tai retentioon vaikuttavaa tekijää. Prosessit ovat kokonaisuuksia, joissa erottumiseen vaikuttavat syöttöliuoksen, erotettavan komponentin ja kalvon ominaisuudet, ja niiden väliset vuorovaikutukset. Työn kokeellisessa osassa koottiin mahdollisimman paljon esimerkkejä, joissa monosakkaridien negatiivinen retentio ilmenee. Muita orgaanisia ja epäorgaanisia yhdisteitä käytettiin 'häiriöyhdisteinä' syöttöliuoksessa monosakkaridien kanssa. Kokeet suoritettiin kahdella laboratoriomittakaavan suodatuslaitteella käyttäen kahta kaupallista nanosuodatuskalvoa. Negatiivinen retentio ilmeni useissa tapauksissa. Permeaattivuon ja 'häiriöyhdisteiden' pitoisuuksien havaittiin vaikuttavan voimakkaasti negatiivisen retention ilmenemiseen.

Effect of Tocopherol Extract, Staphylococcus carnosus Culture, and Celery Concentrate Addition on Quality Parameters of Organic and Conventional Dry-Cured Sausages

The effects of the addition to sausage mix of tocopherols (200 mg/kg), a conventional starter culture with or without Staphylococcus carnosus, celery concentrate (CP) (0.23% and 0.46%), and two doses of nitrate (70 and 140 mg/kg expressed as NaNO(3)) on residual nitrate and nitrite amounts, instrumental CIE Lab color, tocol content, oxidative stability, and overall acceptability were studied in fermented dry-cured sausages after ripening and after storage. Nitrate doses were provided by nitrate-rich CP or a chemical grade source. The lower dose complies with the EU requirements governing the maximum for ingoing amounts in organic meat products. Tocopherol addition protected against oxidation, whereas the nitrate dose, nitrate source, or starter culture had little influence on secondary oxidation values. The residual nitrate and nitrite amounts found in the sausages with the lower nitrate dose were within EU-permitted limits for organic meat products and residual nitrate can be further reduced by the presence of the S. carnosus culture. Color measurements were not affected by the CP dose. Product consumer acceptability was not affected negatively by any of the factors studied. As the two nitrate sources behaved similarly for the parameters studied, CP is a useful alternative to chemical ingredients for organic dry-cured sausage production.

Forecasting tourism demand to Catalonia: neural networks vs. time series models

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourismdemand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling relative to that of time seriesmethods at a regional level. Seasonality and volatility are important features of tourism data, which makes it a particularly favourable context in which to compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official statistical data of overnight stays and tourist arrivals fromall the different countries of origin to Catalonia from 2001 to 2009 is used in the study. When comparing the forecasting accuracy of the different techniques for different time horizons, autoregressive integrated moving average models outperform self-exciting threshold autoregressions and artificial neural network models, especially for shorter horizons. These results suggest that the there is a trade-off between the degree of pre-processing and the accuracy of the forecasts obtained with neural networks, which are more suitable in the presence of nonlinearity in the data. In spite of the significant differences between countries, which can be explained by different patterns of consumer behaviour,we also find that forecasts of tourist arrivals aremore accurate than forecasts of overnight stays.

Organic geochemistry across the Permian-Triassic transition at the Idrijca Valley, Western Slovenia

Bulk and molecular stable C isotopic compositions and biomarker distributions provide evidence for a diverse community of algal and bacterial organisms in the sedimentary organic matter of a carbonate section throughout the Permian-Triassic (P/Tr) transition at the Idrijca Valley, Western Slovenia. The input of algae and bacteria in all the Upper Permian and Lower Scythian samples is represented by the predominance of C-15-C-22 n-alkanes, odd C-number alkylcyclohexanes, C-27 steranes and substantial contents Of C-21-C-30 acyclic isoprenoids. The occurrence of odd long-chain n-alkanes (C-22-C-30) and C29 steranes in all the samples indicate a contribution of continental material. The decrease of C-org and C-carb contents, increase of Rock-Eval oxygen indices, and C-13-enrichment of the kerogen suggest a decrease in anoxia of the uppermost Permian bottom water. The predominance of odd C-number alkylcycloalkanes, C-27 steranes, and C-17 n-alkanes with delta(13)C values similar to-30parts per thousand, and C-13-enrichment of the kerogens in the lowermost Scythian samples are evidence of greater algal productivity. This increased productivity was probably sustained by a high nutrient availability and changes of dissolved CO2 speciation associated to the earliest Triassic transgression. A decrease Of Corg content in the uppermost Scythian samples, associated to a C-13-depletetion in the carbonates (up to 4parts per thousand) and individual n-alkanes (up to 3.4parts per thousand) compared to the Upper Permian samples, indicate lowering of the primary productivity (algae, cyanobacteria) and/or higher degradation of the organic matter. (C) 2003 Elsevier Ltd. All rights reserved.

Chemical chaperones regulate molecular chaperones in vitro and in cells under combined salt and heat stresses.

Salt and heat stresses, which are often combined in nature, induce complementing defense mechanisms. Organisms adapt to high external salinity by accumulating small organic compounds known as osmolytes, which equilibrate cellular osmotic pressure. Osmolytes can also act as "chemical chaperones" by increasing the stability of native proteins and assisting refolding of unfolded polypeptides. Adaptation to heat stress depends on the expression of heat-shock proteins, many of which are molecular chaperones, that prevent protein aggregation, disassemble protein aggregates, and assist protein refolding. We show here that Escherichia coli cells preadapted to high salinity contain increased levels of glycine betaine that prevent protein aggregation under thermal stress. After heat shock, the aggregated proteins, which escaped protection, were disaggregated in salt-adapted cells as efficiently as in low salt. Here we address the effects of four common osmolytes on chaperone activity in vitro. Systematic dose responses of glycine betaine, glycerol, proline, and trehalose revealed a regulatory effect on the folding activities of individual and combinations of chaperones GroEL, DnaK, and ClpB. With the exception of trehalose, low physiological concentrations of proline, glycerol, and especially glycine betaine activated the molecular chaperones, likely by assisting local folding in chaperone-bound polypeptides and stabilizing the native end product of the reaction. High osmolyte concentrations, especially trehalose, strongly inhibited DnaK-dependent chaperone networks, such as DnaK+GroEL and DnaK+ClpB, likely because high viscosity affects dynamic interactions between chaperones and folding substrates and stabilizes protein aggregates. Thus, during combined salt and heat stresses, cells can specifically control protein stability and chaperone-mediated disaggregation and refolding by modulating the intracellular levels of different osmolytes.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Multimodal MRI analysis of structural and functional networks in the human brain : application to two clinical studies : driving abilities under THC intoxication and early white matter changes in FXTAS

Les approches multimodales dans l'imagerie cérébrale non invasive sont de plus en plus considérées comme un outil indispensable pour la compréhension des différents aspects de la structure et de la fonction cérébrale. Grâce aux progrès des techniques d'acquisition des images de Resonance Magnetique et aux nouveaux outils pour le traitement des données, il est désormais possible de mesurer plusieurs paramètres sensibles aux différentes caractéristiques des tissues cérébraux. Ces progrès permettent, par exemple, d'étudier les substrats anatomiques qui sont à la base des processus cognitifs ou de discerner au niveau purement structurel les phénomènes dégénératifs et développementaux. Cette thèse met en évidence l'importance de l'utilisation d'une approche multimodale pour étudier les différents aspects de la dynamique cérébrale grâce à l'application de cette approche à deux études cliniques: l'évaluation structurelle et fonctionnelle des effets aigus du cannabis fumé chez des consommateurs réguliers et occasionnels, et l'évaluation de l'intégrité de la substance grise et blanche chez des jeunes porteurs de la prémutations du gène FMR1 à risque de développer le FXTAS (Fragile-X Tremor Ataxia Syndrome). Nous avons montré que chez les fumeurs occasionnels de cannabis, même à faible concentration du principal composant psychoactif (THC) dans le sang, la performance lors d'une tâche visuo-motrice est fortement diminuée, et qu'il y a des changements dans l'activité des trois réseaux cérébraux impliqués dans les processus cognitifs: le réseau de saillance, le réseau du contrôle exécutif, et le réseau actif par défaut (Default Mode). Les sujets ne sont pas en mesure de saisir les saillances dans l'environnement et de focaliser leur attention sur la tâche. L'augmentation de la réponse hémodynamique dans le cortex cingulaire antérieur suggère une augmentation de l'activité introspective. Une investigation des ef¬fets au niveau cérébral d'une exposition prolongée au cannabis, montre des changements persistants de la substance grise dans les régions associées à la mémoire et au traitement des émotions. Le niveau d'atrophie dans ces structures corrèle avec la consommation de cannabis au cours des trois mois précédant l'étude. Dans la deuxième étude, nous démontrons des altérations structurelles des décennies avant l'apparition du syndrome FXTAS chez des sujets jeunes, asymptomatiques, et porteurs de la prémutation du gène FMR1. Les modifications trouvées peuvent être liées à deux mécanismes différents. Les altérations dans le réseau moteur du cervelet et dans la fimbria de l'hippocampe, suggèrent un effet développemental de la prémutation. Elles incluent aussi une atrophie de la substance grise du lobule VI du cervelet et l'altération des propriétés tissulaires de la substance blanche des projections afférentes correspondantes aux pédoncules cérébelleux moyens. Les lésions diffuses de la substance blanche cérébrale peu¬vent être un marquer précoce du développement de la maladie, car elles sont liées à un phénomène dégénératif qui précède l'apparition des symptômes du FXTAS. - Multimodal brain imaging is becoming a leading tool for understanding different aspects of brain structure and function. Thanks to the advances in Magnetic Resonance imaging (MRI) acquisition schemes and data processing techniques, it is now possible to measure different parameters sensitive to different tissue characteristics. This allows for example to investigate anatomical substrates underlying cognitive processing, or to disentangle, at a pure structural level degeneration and developmental processes. This thesis highlights the importance of using a multimodal approach for investigating different aspects of brain dynamics by applying this approach to two clinical studies: functional and structural assessment of the acute effects of cannabis smoking in regular and occasional users, and grey and white matter assessment in young FMR1 premutation carriers at risk of developing FXTAS. We demonstrate that in occasional smokers cannabis smoking, even at low concentration of the main psychoactive component (THC) in the blood, strongly decrease subjects' performance on a visuo-motor tracking task, and globally alters the activity of the three brain networks involved in cognitive processing: the Salience, the Control Executive, and the Default Mode networks. Subjects are unable to capture saliences in the environment and to orient attention to the task; the increase in Hemodynamic Response in the Anterior Cingulate Cortex suggests an increase in self-oriented mental activity. A further investigation on long term exposure to cannabis, shows a persistent grey matter modification in brain regions associated with memory and affective processing. The degree of atrophy in these structures also correlates with the estimation of drug use in the three months prior the participation to the study. In the second study we demonstrate structural changes in young asymptomatic premutation carriers decades before the onset of FXTAS that might be related to two different mechanisms. Alteration of the cerebellar motor network and of the hippocampal fimbria/ fornix, may reflect a potential neurodevelopmental effect of the premutation. These include grey matter atrophy in lobule VI and modification of white matter tissue property in the corresponding afferent projections through the Middle Cerebellar Peduncles. Diffuse hemispheric white matter lesions that seem to appear closer to the onset of FXTAS and be related to a neurodegenerative phenomenon may mark the imminent onset of FXTAS.

The Possibilities of IP Networks in Strategic Partnership Development

This study focuses on the status of using the Internet in partnership development. The aim is to find out howthe parties in partnership can benefit from the available data networks (the Internet, Intranet and Extranet). The study also explains what the typical practices at the moment are and what features might be exploitable in the future. The research problem is to find out whether there are any possibilities to utilize the web more than is done at the moment. This study is a preliminary study for a more extensive study on the topic 'Information Technology in Business Relationships'.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.