On iterative performance of LDPC and Root-LDPC codes over block-fading channels

This paper presents our investigation on iterativedecoding performances of some sparse-graph codes on block-fading Rayleigh channels. The considered code ensembles are standard LDPC codes and Root-LDPC codes, first proposed in and shown to be able to attain the full transmission diversity. We study the iterative threshold performance of those codes as a function of fading gains of the transmission channel and propose a numerical approximation of the iterative threshold versus fading gains, both both LDPC and Root-LDPC codes.Also, we show analytically that, in the case of 2 fading blocks,the iterative threshold root of Root-LDPC codes is proportional to (α1 α2)1, where α1 and α2 are corresponding fading gains.From this result, the full diversity property of Root-LDPC codes immediately follows.

Using qualia information to identify lexical semantic classes in an unsupervised clustering task

Acquiring lexical information is a complex problem, typically approached by relying on a number of contexts to contribute information for classification. One of the first issues to address in this domain is the determination of such contexts. The work presented here proposes the use of automatically obtained FORMAL role descriptors as features used to draw nouns from the same lexical semantic class together in an unsupervised clustering task. We have dealt with three lexical semantic classes (HUMAN, LOCATION and EVENT) in English. The results obtained show that it is possible to discriminate between elements from different lexical semantic classes using only FORMAL role information, hence validating our initial hypothesis. Also, iterating our method accurately accounts for fine-grained distinctions within lexical classes, namely distinctions involving ambiguous expressions. Moreover, a filtering and bootstrapping strategy employed in extracting FORMAL role descriptors proved to minimize effects of sparse data and noise in our task.

Peroxisome proliferator-activated receptor beta/delta as a therapeutic target for metabolic diseases.

The peroxisome proliferator-activated receptor (PPAR) family comprises three distinct isotypes: PPARalpha, PPARbeta/delta and PPARgamma. PPARs are nuclear hormone receptors that mediate the effects of fatty acids and their derivatives at the transcriptional level. Until recently, the characterisation of the important role of PPARalpha in fatty acid oxidation and of PPARgamma in lipid storage contrasted with the sparse information concerning PPARbeta/delta. However, evidence is now emerging for a role of PPARbeta/delta in tissue repair and energy homeostasis. Experiments with tissue-specific overexpression of PPARbeta/delta or treatment of mice with selective PPARbeta/delta agonists demonstrated that activation of PPARbeta/delta in vivo increases lipid catabolism in skeletal muscle, heart and adipose tissue and improves the serum lipid profile and insulin sensitivity in several animal models. PPARbeta/delta activation also prevents the development of obesity and improves cholesterol homeostasis in obesity-prone mouse models. These new insights into PPARbeta/delta functions suggest that targeting PPARbeta/delta may be helpful for treating disorders associated with the metabolic syndrome. Although these perspectives are promising, several independent and contradictory reports raise concerns about the safety of PPARbeta/delta ligands with respect to tumourigenic activity in the gut. Thus, it appears that further exploration of PPARbeta/delta functions is necessary to better define its potential as a therapeutic target.

Kaupungin ja maaseudun vuorovaikutus alueellisessa kehittämispolitiikassa

In Finland, European Union membership and economic globalisation have changed the position of regions from closed territorial systems to nodes of open international networks. The increasing complexity of cities as globalised knowledge centres and functionally specialised and diversified rural areas, and on the other hand growing disparities between prosperous urban cores and lagging peripheral areas are also essential features in contemporary regional development. These trends have produced new needs to promote mutual dialogue between cities and the countryside in western market economies. Urban-rural interaction is an idea which was developed in the late 1990s within regional policy to pull together these new challenges to regional development and handle cities and the countryside as a whole. The aim of my study is to conceptualise the idea of urban-rural interaction, explain the phenomenon theoretically, clarify past and present urban and rural development and analyse regional policies from the interaction angle. The ultimate purpose is to illustrate the existence and nature of particular interaction policy in a globalising society. The general method is discourse analysis, which I use in three cases: Central Finland, South-Ostrobothnia and South-West Finland. Theoretically I have a two-dimensional approach. On the first hand I use World-System theory to explain how the global economy is moulding urban and rural structures at the regional level. On the other hand I use regime theory to explain local political actions and practises between cities and the countryside under the overlapping pressures deriving from reformulated regional structures and policies.

Adaptation to globalisation in Finland has been carried out by strengthening urban centres. The stress in regional policy has been in urban development. The development of the countryside has mostly been implemented by a separate rural policy. At the end of the 1990s and early 2000s Finnish cities have actually shown themselves to be competitive in global markets. The drawbacks of the new growth centre policy have been the sparse network of prosperous cities and their weak spreading effects, which have hindered comprehensive regional development. Tensions between urban and rural areas have also deepened. In this situation the interaction policy is used as a way of balancing development and moderate conflicts within the regions. From this point of view urban-rural interaction can be seen as a way of tackling the challenges of globalisation.

On the other hand the results emphasise that actors involved in regional development still believe, although the hegemonic discourse is on urban policy, that there are opportunities to stimulate progress in the countryside as well. In the situation where regional authorities control development resources, rural development can be successful only if rural actors manage to establish fruitful relationships with their urban partners. This is also the weakness of the programme-based regional policy. If rural municipalities or other actors are for any reason incapable of building development regimes with cities, the offers of interaction policy will be useless.

The problem of the interaction policy is that the focus and methods of it have so far been rather underdeveloped. In order to improve the efficiency of the interaction policy, further research should concentrate on the social processes which define the position of cities and the countryside as partners of interaction, and practises which promote or prohibit the possibilities of developing the interaction policy. The efforts to define different contents of urban-rural interaction or promote interaction projects should not have such an important role in the future as they have had so far. Instead, the focus of interaction policy should be on questions such as how to manage the political tensions between town and country and how to create a positive atmosphere for regional policy where the needs of urban and rural development are promoted equally.

The oceanic base of slope record of the Permian-Triassic crisis: view from Tethys (Oman)

The Oman Mountains provide some of the best sections of Permian and Triassic sediments from ocean sea floor to base-of-slope environments related to the distal South Tethyan margin. The central part of the range exposes the Buday'ah section of oceanic sediments in the so-called "Hawasina allochtons". The locality of Wadi Maqam in the north-western part of the Oman Mountains is among places where the thick Permian-Triassic base-of-slope sediments is exposed (Baud et al., 2001). Overlying 400 m of middle Permian limestones and dolomites, the upper Permian sediments consist of 50 m of ≈ 10 cm thick beds of cherts and dolomites rich in sponge spicules. The top of the Permian units is well bioturbated lime mudstone-wackestone, devoid of cherts and dated as late Changhsingian (Krystyn in Richoz et al., 2005). The boundary yellow shales are overlain by very thinly bedded, laminated microbial platy lime mudstone with H. parvus. The dramatic loss of the burrowing infauna indicates the appearance of oxygen-poor water. These Induan sediments are about 25 m thick and show at the top the first calcirudites, commonly clast-supported (edge-wise conglomerates), and are characterized by tabular clasts representing the sub- in situ reworking of the laminated, platy calcilutite. The very thick Smithian overlying litho-unit (up to 900 m) marks the onset on the base-of-slope of a deep-marine basin in which carbonate submarine fan deposits developed This very thick unit consists essentially of platy limestones, calcarenites and calcirudites. It comprises mainly grey-beige calcilutite, laminated and flaggy, interbedded with sparse beds of fine-grained calcarenite in cm beds. Channelized beds of intraformational calcirudite are also part of this succession which constitutes the greater part of the outcrop available. During the Spathian to Anisian, the sedimentation changes to terrigenous mudstone and siltstone that ended with Ladinian radiolarites.

Assignment strategies for large proteins by magic-angle spinning NMR: the 21-kDa disulfide-bond-forming enzyme DsbA.

We present strategies for chemical shift assignments of large proteins by magic-angle spinning solid-state NMR, using the 21-kDa disulfide-bond-forming enzyme DsbA as prototype. Previous studies have demonstrated that complete de novo assignments are possible for proteins up to approximately 17 kDa, and partial assignments have been performed for several larger proteins. Here we show that combinations of isotopic labeling strategies, high field correlation spectroscopy, and three-dimensional (3D) and four-dimensional (4D) backbone correlation experiments yield highly confident assignments for more than 90% of backbone resonances in DsbA. Samples were prepared as nanocrystalline precipitates by a dialysis procedure, resulting in heterogeneous linewidths below 0.2 ppm. Thus, high magnetic fields, selective decoupling pulse sequences, and sparse isotopic labeling all improved spectral resolution. Assignments by amino acid type were facilitated by particular combinations of pulse sequences and isotopic labeling; for example, transferred echo double resonance experiments enhanced sensitivity for Pro and Gly residues; [2-(13)C]glycerol labeling clarified Val, Ile, and Leu assignments; in-phase anti-phase correlation spectra enabled interpretation of otherwise crowded Glx/Asx side-chain regions; and 3D NCACX experiments on [2-(13)C]glycerol samples provided unique sets of aromatic (Phe, Tyr, and Trp) correlations. Together with high-sensitivity CANCOCA 4D experiments and CANCOCX 3D experiments, unambiguous backbone walks could be performed throughout the majority of the sequence. At 189 residues, DsbA represents the largest monomeric unit for which essentially complete solid-state NMR assignments have so far been achieved. These results will facilitate studies of nanocrystalline DsbA structure and dynamics and will enable analysis of its 41-kDa covalent complex with the membrane protein DsbB, for which we demonstrate a high-resolution two-dimensional (13)C-(13)C spectrum.

25-hydroxyvitamin D concentration is inversely associated with serum MMP-9 in a cross-sectional study of African American ESRD patients.

BACKGROUND: Circulating 25-hydroxyvitamin D [25(OH)D] concentration is inversely associated with peripheral arterial disease and hypertension. Vascular remodeling may play a role in this association, however, data relating vitamin D level to specific remodeling biomarkers among ESRD patients is sparse. We tested whether 25(OH)D concentration is associated with markers of vascular remodeling and inflammation in African American ESRD patients.METHODS: We conducted a cross-sectional study among ESRD patients receiving maintenance hemodialysis within Emory University-affiliated outpatient hemodialysis units. Demographic, clinical and dialysis treatment data were collected via direct patient interview and review of patients records at the time of enrollment, and each patient gave blood samples. Associations between 25(OH)D and biomarker concentrations were estimated in univariate analyses using Pearson's correlation coefficients and in multivariate analyses using linear regression models. 25(OH) D concentration was entered in multivariate linear regression models as a continuous variable and binary variable (<15 ng/ml and =15 ng/ml). Adjusted estimate concentrations of biomarkers were compared between 25(OH) D groups using analysis of variance (ANOVA). Finally, results were stratified by vascular access type.RESULTS: Among 91 patients, mean (standard deviation) 25(OH)D concentration was 18.8 (9.6) ng/ml, and was low (<15 ng/ml) in 43% of patients. In univariate analyses, low 25(OH) D was associated with lower serum calcium, higher serum phosphorus, and higher LDL concentrations. 25(OH) D concentration was inversely correlated with MMP-9 concentration (r = -0.29, p = 0.004). In multivariate analyses, MMP-9 concentration remained negatively associated with 25(OH) D concentration (P = 0.03) and anti-inflammatory IL-10 concentration positively correlated with 25(OH) D concentration (P = 0.04).CONCLUSIONS: Plasma MMP-9 and circulating 25(OH) D concentrations are significantly and inversely associated among ESRD patients. This finding may suggest a potential mechanism by which low circulating 25(OH) D functions as a cardiovascular risk factor.

Changing landscapes of Switzerland: assessing effects of historic and future land uses and land covers on the occurrence of selected butterfly species

Summary Landscapes are continuously changing. Natural forces of change such as heavy rainfall and fires can exert lasting influences on their physical form. However, changes related to human activities have often shaped landscapes more distinctly. In Western Europe, especially modern agricultural practices and the expanse of overbuilt land have left their marks in the landscapes since the middle of the 20th century. In the recent years men realised that mare and more changes that were formerly attributed to natural forces might indirectly be the result of their own action. Perhaps the most striking landscape change indirectly driven by human activity we can witness in these days is the large withdrawal of Alpine glaciers. Together with the landscapes also habitats of animal and plant species have undergone vast and sometimes rapid changes that have been hold responsible for the ongoing loss of biodiversity. Thereby, still little knowledge is available about probable effects of the rate of landscape change on species persistence and disappearance. Therefore, the development and speed of land use/land cover in the Swiss communes between the 1950s and 1990s were reconstructed using 10 parameters from agriculture and housing censuses, and were further correlated with changes in butterfly species occurrences. Cluster analyses were used to detect spatial patterns of change on broad spatial scales. Thereby, clusters of communes showing similar changes or transformation rates were identified for single decades and put into a temporally dynamic sequence. The obtained picture on the changes showed a prevalent replacement of non-intensive agriculture by intensive practices, a strong spreading of urban communes around city centres, and transitions towards larger farm sizes in the mountainous areas. Increasing transformation rates toward more intensive agricultural managements were especially found until the 1970s, whereas afterwards the trends were commonly negative. However, transformation rates representing the development of residential buildings showed positive courses at any time. The analyses concerning the butterfly species showed that grassland species reacted sensitively to the density of livestock in the communes. This might indicate the augmented use of dry grasslands as cattle pastures that show altered plant species compositions. Furthermore, these species also decreased in communes where farms with an agricultural area >5ha have disappeared. The species of the wetland habitats were favoured in communes with smaller fractions of agricultural areas and lower densities of large farms (>10ha) but did not show any correlation to transformation rates. It was concluded from these analyses that transformation rates might influence species disappearance to a certain extent but that states of the environmental predictors might generally outweigh the importance of the corresponding rates. Information on the current distribution of species is evident for nature conservation. Planning authorities that define priority areas for species protection or examine and authorise construction projects need to know about the spatial distribution of species. Hence, models that simulate the potential spatial distribution of species have become important decision tools. The underlying statistical analyses such as the widely used generalised linear models (GLM) often rely on binary species presence-absence data. However, often only species presence data have been colleted, especially for vagrant, rare or cryptic species such as butterflies or reptiles. Modellers have thus introduced randomly selected absence data to design distribution models. Yet, selecting false absence data might bias the model results. Therefore, we investigated several strategies to select more reliable absence data to model the distribution of butterfly species based on historical distribution data. The results showed that better models were obtained when historical data from longer time periods were considered. Furthermore, model performance was additionally increased when long-term data of species that show similar habitat requirements as the modelled species were used. This successful methodological approach was further applied to assess consequences of future landscape changes on the occurrence of butterfly species inhabiting dry grasslands or wetlands. These habitat types have been subjected to strong deterioration in the recent decades, what makes their protection a future mission. Four spatially explicit scenarios that described (i) ongoing land use changes as observed between 1985 and 1997, (ii) liberalised agricultural markets, and (iii) slightly and (iv) strongly lowered agricultural production provided probable directions of landscape change. Current species-environment relationships were derived from a statistical model and used to predict future occurrence probabilities in six major biogeographical regions in Switzerland, comprising the Jura Mountains, the Plateau, the Northern and Southern Alps, as well as the Western and Eastern Central Alps. The main results were that dry grasslands species profited from lowered agricultural production, whereas overgrowth of open areas in the liberalisation scenario might impair species occurrence. The wetland species mostly responded with decreases in their occurrence probabilities in the scenarios, due to a loss of their preferred habitat. Further analyses about factors currently influencing species occurrences confirmed anthropogenic causes such as urbanisation, abandonment of open land, and agricultural intensification. Hence, landscape planning should pay more attention to these forces in areas currently inhabited by these butterfly species to enable sustainable species persistence. In this thesis historical data were intensively used to reconstruct past developments and to make them useful for current investigations. Yet, the availability of historical data and the analyses on broader spatial scales has often limited the explanatory power of the conducted analyses. Meaningful descriptors of former habitat characteristics and abundant species distribution data are generally sparse, especially for fine scale analyses. However, this situation can be ameliorated by broadening the extent of the study site and the used grain size, as was done in this thesis by considering the whole of Switzerland with its communes. Nevertheless, current monitoring projects and data recording techniques are promising data sources that might allow more detailed analyses about effects of long-term species reactions on landscape changes in the near future. This work, however, also showed the value of historical species distribution data as for example their potential to locate still unknown species occurrences. The results might therefore contribute to further research activities that investigate current and future species distributions considering the immense richness of historical distribution data. Résumé Les paysages changent continuellement. Des farces naturelles comme des pluies violentes ou des feux peuvent avoir une influence durable sur la forme du paysage. Cependant, les changements attribués aux activités humaines ont souvent modelé les paysages plus profondément. Depuis les années 1950 surtout, les pratiques agricoles modernes ou l'expansion des surfaces d'habitat et d'infrastructure ont caractérisé le développement du paysage en Europe de l'Ouest. Ces dernières années, l'homme a commencé à réaliser que beaucoup de changements «naturels » pourraient indirectement résulter de ses propres activités. Le changement de paysage le plus apparent dont nous sommes témoins de nos jours est probablement l'immense retraite des glaciers alpins. Avec les paysages, les habitats des animaux et des plantes ont aussi été exposés à des changements vastes et quelquefois rapides, tenus pour coresponsable de la continuelle diminution de la biodiversité. Cependant, nous savons peu des effets probables de la rapidité des changements du paysage sur la persistance et la disparition des espèces. Le développement et la rapidité du changement de l'utilisation et de la couverture du sol dans les communes suisses entre les années 50 et 90 ont donc été reconstruits au moyen de 10 variables issues des recensements agricoles et résidentiels et ont été corrélés avec des changements de présence des papillons diurnes. Des analyses de groupes (Cluster analyses) ont été utilisées pour détecter des arrangements spatiaux de changements à l'échelle de la Suisse. Des communes avec des changements ou rapidités comparables ont été délimitées pour des décennies séparées et ont été placées en séquence temporelle, en rendrent une certaine dynamique du changement. Les résultats ont montré un remplacement répandu d'une agriculture extensive des pratiques intensives, une forte expansion des faubourgs urbains autour des grandes cités et des transitions vers de plus grandes surfaces d'exploitation dans les Alpes. Dans le cas des exploitations agricoles, des taux de changement croissants ont été observés jusqu'aux années 70, alors que la tendance a généralement été inversée dans les années suivantes. Par contre, la vitesse de construction des nouvelles maisons a montré des courbes positives pendant les 50 années. Les analyses sur la réaction des papillons diurnes ont montré que les espèces des prairies sèches supportaient une grande densité de bétail. Il est possible que dans ces communes beaucoup des prairies sèches aient été fertilisées et utilisées comme pâturages, qui ont une autre composition floristique. De plus, les espèces ont diminué dans les communes caractérisées par une rapide perte des fermes avec une surface cultivable supérieure à 5 ha. Les espèces des marais ont été favorisées dans des communes avec peu de surface cultivable et peu de grandes fermes, mais n'ont pas réagi aux taux de changement. Il en a donc été conclu que la rapidité des changements pourrait expliquer les disparitions d'espèces dans certains cas, mais que les variables prédictives qui expriment des états pourraient être des descripteurs plus importants. Des informations sur la distribution récente des espèces sont importantes par rapport aux mesures pour la conservation de la nature. Pour des autorités occupées à définir des zones de protection prioritaires ou à autoriser des projets de construction, ces informations sont indispensables. Les modèles de distribution spatiale d'espèces sont donc devenus des moyens de décision importants. Les méthodes statistiques courantes comme les modèles linéaires généralisés (GLM) demandent des données de présence et d'absence des espèces. Cependant, souvent seules les données de présence sont disponibles, surtout pour les animaux migrants, rares ou cryptiques comme des papillons ou des reptiles. C'est pourquoi certains modélisateurs ont choisi des absences au hasard, avec le risque d'influencer le résultat en choisissant des fausses absences. Nous avons établi plusieurs stratégies, basées sur des données de distribution historique des papillons diurnes, pour sélectionner des absences plus fiables. Les résultats ont démontré que de meilleurs modèles pouvaient être obtenus lorsque les données proviennent des périodes de temps plus longues. En plus, la performance des modèles a pu être augmentée en considérant des données de distribution à long terme d'espèces qui occupent des habitats similaires à ceux de l'espèce cible. Vu le succès de cette stratégie, elle a été utilisée pour évaluer les effets potentiels des changements de paysage futurs sur la distribution des papillons des prairies sèches et marais, deux habitats qui ont souffert de graves détériorations. Quatre scénarios spatialement explicites, décrivant (i) l'extrapolation des changements de l'utilisation de sol tels qu'observés entre 1985 et 1997, (ii) la libéralisation des marchés agricoles, et une production agricole (iii) légèrement amoindrie et (iv) fortement diminuée, ont été utilisés pour générer des directions de changement probables. Les relations actuelles entre la distribution des espèces et l'environnement ont été déterminées par le biais des modèles statistiques et ont été utilisées pour calculer des probabilités de présence selon les scénarios dans six régions biogéographiques majeures de la Suisse, comportant le Jura, le Plateau, les Alpes du Nord, du Sud, centrales orientales et centrales occidentales. Les résultats principaux ont montré que les espèces des prairies sèches pourraient profiter d'une diminution de la production agricole, mais qu'elles pourraient aussi disparaître à cause de l'embroussaillement des terres ouvertes dû à la libéralisation des marchés agricoles. La probabilité de présence des espèces de marais a décrû à cause d'une perte générale des habitats favorables. De plus, les analyses ont confirmé que des causes humaines comme l'urbanisation, l'abandon des terres ouvertes et l'intensification de l'agriculture affectent actuellement ces espèces. Ainsi ces forces devraient être mieux prises en compte lors de planifications paysagères, pour que ces papillons diurnes puissent survivre dans leurs habitats actuels. Dans ce travail de thèse, des données historiques ont été intensivement utilisées pour reconstruire des développements anciens et pour les rendre utiles à des recherches contemporaines. Cependant, la disponibilité des données historiques et les analyses à grande échelle ont souvent limité le pouvoir explicatif des analyses. Des descripteurs pertinents pour caractériser les habitats anciens et des données suffisantes sur la distribution des espèces sont généralement rares, spécialement pour des analyses à des échelles fores. Cette situation peut être améliorée en augmentant l'étendue du site d'étude et la résolution, comme il a été fait dans cette thèse en considérant toute la Suisse avec ses communes. Cependant, les récents projets de surveillance et les techniques de collecte de données sont des sources prometteuses, qui pourraient permettre des analyses plus détaillés sur les réactions à long terme des espèces aux changements de paysage dans le futur. Ce travail a aussi montré la valeur des anciennes données de distribution, par exemple leur potentiel pour aider à localiser des' présences d'espèces encore inconnues. Les résultats peuvent contribuer à des activités de recherche à venir, qui étudieraient les distributions récentes ou futures d'espèces en considérant l'immense richesse des données de distribution historiques.

Nets: Network estimation for time series

This work proposes novel network analysis techniques for multivariate time series.We define the network of a multivariate time series as a graph where verticesdenote the components of the process and edges denote non zero long run partialcorrelations. We then introduce a two step LASSO procedure, called NETS, toestimate high dimensional sparse Long Run Partial Correlation networks. This approachis based on a VAR approximation of the process and allows to decomposethe long run linkages into the contribution of the dynamic and contemporaneousdependence relations of the system. The large sample properties of the estimatorare analysed and we establish conditions for consistent selection and estimation ofthe non zero long run partial correlations. The methodology is illustrated with anapplication to a panel of U.S. bluechips.

Adaptation to marginal habitats

The ability to adapt to marginal habitats, in which survival and reproduction are initially poor, plays a crucial role in the evolution of ecological niches and species ranges. Adaptation to marginal habitats may be limited by genetic, developmental, and functional constraints, but also by consequences of demographic characteristics of marginal populations. Marginal populations are often sparse, fragmented, prone to local extinctions, or are demographic sinks subject to high immigration from high-quality core habitats. This makes them demographically and genetically dependent on core habitats and prone to gene flow counteracting local selection. Theoretical and empirical research in the past decade has advanced our understanding of conditions that favor adaptation to marginal habitats despite those limitations. This review is an attempt at synthesis of those developments and of the emerging conceptual framework.

Novel methods improve prediction of species' distributions from occurrence data

Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

Not all inflammatory markers are linked to kidney function: results from a population-based study.

BACKGROUND: Several studies have reported increased levels of inflammatory biomarkers in chronic kidney disease (CKD), but data from the general population are sparse. In this study, we assessed levels of the inflammatory markers C-reactive protein (hsCRP), tumor necrosis factor α (TNF-α), interleukin (IL)-1β and IL-6 across all ranges of renal function. METHODS: We conducted a cross-sectional study in a random sample of 6,184 Caucasian subjects aged 35-75 years in Lausanne, Switzerland. Serum levels of hsCRP, TNF-α, IL-6, and IL-1β were measured in 6,067 participants (98.1%); serum creatinine-based estimated glomerular filtration rate (eGFR(creat), CKD-EPI formula) was used to assess renal function, and albumin/creatinine ratio on spot morning urine to assess microalbuminuria (MAU). RESULTS: Higher serum levels of IL-6, TNF-α and hsCRP and lower levels of IL-1β were associated with a lower renal function, CKD (eGFR(creat) <60 ml/min/1.73 m(2); n = 283), and MAU (n = 583). In multivariate linear regression analysis adjusted for age, sex, hypertension, smoking, diabetes, body mass index, lipids, antihypertensive and hypolipemic therapy, only log-transformed TNF-α remained independently associated with lower renal function (β -0.54 ±0.19). In multivariate logistic regression analysis, higher TNF-α levels were associated with CKD (OR 1.17; 95% CI 1.01-1.35), whereas higher levels of IL-6 (OR 1.09; 95% CI 1.02-1.16) and hsCRP (OR 1.21; 95% CI 1.10-1.32) were associated with MAU. CONCLUSION: We did not confirm a significant association between renal function and IL-6, IL-1β and hsCRP in the general population. However, our results demonstrate a significant association between TNF-α and renal function, suggesting a potential link between inflammation and the development of CKD. These data also confirm the association between MAU and inflammation.

Applicability of a distributed watershed pollution model in a data-poor environment in Santa Catarina State, Brazil

Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Respiratory nitric oxide and pulmonary artery pressure in children of aymara and European ancestry at high altitude.

Invasive studies suggest that healthy children living at high altitude display pulmonary hypertension, but the data to support this assumption are sparse. Nitric oxide (NO) synthesized by the respiratory epithelium regulates pulmonary artery pressure, and its synthesis was reported to be increased in Aymara high-altitude dwellers. We hypothesized that pulmonary artery pressure will be lower in Aymara children than in children of European ancestry at high altitude, and that this will be related to increased respiratory NO. We therefore compared pulmonary artery pressure and exhaled NO (a marker of respiratory epithelial NO synthesis) between large groups of healthy children of Aymara (n = 200; mean +/- SD age, 9.5 +/- 3.6 years) and European ancestry (n = 77) living at high altitude (3,600 to 4,000 m). We also studied a group of European children (n = 29) living at low altitude. The systolic right ventricular to right atrial pressure gradient in the Aymara children was normal, even though significantly higher than the gradient measured in European children at low altitude (22.5 +/- 6.1 mm Hg vs 17.7 +/- 3.1 mm Hg, p < 0.001). In children of European ancestry studied at high altitude, the pressure gradient was 33% higher than in the Aymara children (30.0 +/- 5.3 mm Hg vs 22.5 +/- 6.1 mm Hg, p < 0.0001). In contrast to what was expected, exhaled NO tended to be lower in Aymara children than in European children living at the same altitude (12.4 +/- 8.8 parts per billion [ppb] vs 16.1 +/- 11.1 ppb, p = 0.06) and was not related to pulmonary artery pressure in either group. Aymara children are protected from hypoxic pulmonary hypertension at high altitude. This protection does not appear to be related to increased respiratory NO synthesis.