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.

Cheminformatic studies of molecular properties and their influence on bioactivity in the context of drug discovery

Molecular shape has long been known to be an important property for the process of molecular recognition. Previous studies postulated the existence of a drug-like shape space that could be used to artificially bias the composition of screening libraries, with the aim to increase the chance of success in Hit Identification. In this work, it was analysed to which extend this assumption holds true. Normalized Principal Moments of Inertia Ratios (NPRs) have been used to describe the molecular shape of small molecules. It was investigated, whether active molecules of diverse targets are located in preferred subspaces of the NPR shape space. Results illustrated a significantly stronger clustering than could be expected by chance, with parts of the space unlikely to be occupied by active compounds. Furthermore, a strong enrichment of elongated, rather flat shapes could be observed, while globular compounds were highly underrepresented. This was confirmed for a wide range of small molecule datasets from different origins. Active compounds exhibited a high overlap in their shape distributions across different targets, making a purely shape­ based discrimination very difficult. An additional perspective was provided by comparing the shapes of protein binding pockets with those of their respective ligands. Although more globular than their ligands, it was observed that binding sites shapes exhibited a similarly skewed distribution in shape space: spherical shapes were highly underrepresented. This was different for unoccupied binding pockets of smaller size. These were on the contrary identified to possess a more globular shape. The relation between shape complementarity and exhibited bioactivity was analysed; a moderate correlation between bioactivity and parameters including pocket coverage, distance in shape space, and others could be identified, which reflects the importance of shape complementarity. However, this also suggests that other aspects are of relevance for molecular recognition. A subsequent analysis assessed if and how shape and volume information retrieved from pocket or respective reference ligands could be used as a pre-filter in a virtual screening approach. ln Lead Optimization compounds need to get optimized with respect to a variety of pararneters. Here, the availability of past success stories is very valuable, as they can guide medicinal chemists during their analogue synthesis plans. However, although of tremendous interest for the public domain, so far only large corporations had the ability to mine historical knowledge in their proprietary databases. With the aim to provide such information, the SwissBioisostere database was developed and released during this thesis. This database contains information on 21,293,355 performed substructural exchanges, corresponding to 5,586,462 unique replacements that have been measured in 35,039 assays against 1,948 molecular targets representing 30 target classes, and on their impact on bioactivity . A user-friendly interface was developed that provides facile access to these data and is accessible at http//www.swissbioisostere.ch. The ChEMBL database was used as primary data source of bioactivity information. Matched molecular pairs have been identified in the extracted and cleaned data. Success-based scores were developed and integrated into the database to allow re-ranking of proposed replacements by their past outcomes. It was analysed to which degree these scores correlate with chemical similarity of the underlying fragments. An unexpectedly weak relationship was detected and further investigated. Use cases of this database were envisioned, and functionalities implemented accordingly: replacement outcomes are aggregatable at the assay level, and it was shawn that an aggregation at the target or target class level could also be performed, but should be accompanied by a careful case-by-case assessment. It was furthermore observed that replacement success depends on the activity of the starting compound A within a matched molecular pair A-B. With increasing potency the probability to lose bioactivity through any substructural exchange was significantly higher than in low affine binders. A potential existence of a publication bias could be refuted. Furthermore, often performed medicinal chemistry strategies for structure-activity-relationship exploration were analysed using the acquired data. Finally, data originating from pharmaceutical companies were compared with those reported in the literature. It could be seen that industrial medicinal chemistry can access replacement information not available in the public domain. In contrast, a large amount of often-performed replacements within companies could also be identified in literature data. Preferences for particular replacements differed between these two sources. The value of combining different endpoints in an evaluation of molecular replacements was investigated. The performed studies highlighted furthermore that there seem to exist no universal substructural replacement that always retains bioactivity irrespective of the biological environment. A generalization of bioisosteric replacements seems therefore not possible. - La forme tridimensionnelle des molécules a depuis longtemps été reconnue comme une propriété importante pour le processus de reconnaissance moléculaire. Des études antérieures ont postulé que les médicaments occupent préférentiellement un sous-ensemble de l'espace des formes des molécules. Ce sous-ensemble pourrait être utilisé pour biaiser la composition de chimiothèques à cribler, dans le but d'augmenter les chances d'identifier des Hits. L'analyse et la validation de cette assertion fait l'objet de cette première partie. Les Ratios de Moments Principaux d'Inertie Normalisés (RPN) ont été utilisés pour décrire la forme tridimensionnelle de petites molécules de type médicament. Il a été étudié si les molécules actives sur des cibles différentes se co-localisaient dans des sous-espaces privilégiés de l'espace des formes. Les résultats montrent des regroupements de molécules incompatibles avec une répartition aléatoire, avec certaines parties de l'espace peu susceptibles d'être occupées par des composés actifs. Par ailleurs, un fort enrichissement en formes allongées et plutôt plates a pu être observé, tandis que les composés globulaires étaient fortement sous-représentés. Cela a été confirmé pour un large ensemble de compilations de molécules d'origines différentes. Les distributions de forme des molécules actives sur des cibles différentes se recoupent largement, rendant une discrimination fondée uniquement sur la forme très difficile. Une perspective supplémentaire a été ajoutée par la comparaison des formes des ligands avec celles de leurs sites de liaison (poches) dans leurs protéines respectives. Bien que plus globulaires que leurs ligands, il a été observé que les formes des poches présentent une distribution dans l'espace des formes avec le même type d'asymétrie que celle observée pour les ligands: les formes sphériques sont fortement sous­ représentées. Un résultat différent a été obtenu pour les poches de plus petite taille et cristallisées sans ligand: elles possédaient une forme plus globulaire. La relation entre complémentarité de forme et bioactivité a été également analysée; une corrélation modérée entre bioactivité et des paramètres tels que remplissage de poche, distance dans l'espace des formes, ainsi que d'autres, a pu être identifiée. Ceci reflète l'importance de la complémentarité des formes, mais aussi l'implication d'autres facteurs. Une analyse ultérieure a évalué si et comment la forme et le volume d'une poche ou de ses ligands de référence pouvaient être utilisés comme un pré-filtre dans une approche de criblage virtuel. Durant l'optimisation d'un Lead, de nombreux paramètres doivent être optimisés simultanément. Dans ce contexte, la disponibilité d'exemples d'optimisations réussies est précieuse, car ils peuvent orienter les chimistes médicinaux dans leurs plans de synthèse par analogie. Cependant, bien que d'un extrême intérêt pour les chercheurs dans le domaine public, seules les grandes sociétés pharmaceutiques avaient jusqu'à présent la capacité d'exploiter de telles connaissances au sein de leurs bases de données internes. Dans le but de remédier à cette limitation, la base de données SwissBioisostere a été élaborée et publiée dans le domaine public au cours de cette thèse. Cette base de données contient des informations sur 21 293 355 échanges sous-structuraux observés, correspondant à 5 586 462 remplacements uniques mesurés dans 35 039 tests contre 1948 cibles représentant 30 familles, ainsi que sur leur impact sur la bioactivité. Une interface a été développée pour permettre un accès facile à ces données, accessible à http:/ /www.swissbioisostere.ch. La base de données ChEMBL a été utilisée comme source de données de bioactivité. Une version modifiée de l'algorithme de Hussain et Rea a été implémentée pour identifier les Matched Molecular Pairs (MMP) dans les données préparées au préalable. Des scores de succès ont été développés et intégrés dans la base de données pour permettre un reclassement des remplacements proposés selon leurs résultats précédemment observés. La corrélation entre ces scores et la similarité chimique des fragments correspondants a été étudiée. Une corrélation plus faible qu'attendue a été détectée et analysée. Différents cas d'utilisation de cette base de données ont été envisagés, et les fonctionnalités correspondantes implémentées: l'agrégation des résultats de remplacement est effectuée au niveau de chaque test, et il a été montré qu'elle pourrait également être effectuée au niveau de la cible ou de la classe de cible, sous réserve d'une analyse au cas par cas. Il a en outre été constaté que le succès d'un remplacement dépend de l'activité du composé A au sein d'une paire A-B. Il a été montré que la probabilité de perdre la bioactivité à la suite d'un remplacement moléculaire quelconque est plus importante au sein des molécules les plus actives que chez les molécules de plus faible activité. L'existence potentielle d'un biais lié au processus de publication par articles a pu être réfutée. En outre, les stratégies fréquentes de chimie médicinale pour l'exploration des relations structure-activité ont été analysées à l'aide des données acquises. Enfin, les données provenant des compagnies pharmaceutiques ont été comparées à celles reportées dans la littérature. Il a pu être constaté que les chimistes médicinaux dans l'industrie peuvent accéder à des remplacements qui ne sont pas disponibles dans le domaine public. Par contre, un grand nombre de remplacements fréquemment observés dans les données de l'industrie ont également pu être identifiés dans les données de la littérature. Les préférences pour certains remplacements particuliers diffèrent entre ces deux sources. L'intérêt d'évaluer les remplacements moléculaires simultanément selon plusieurs paramètres (bioactivité et stabilité métabolique par ex.) a aussi été étudié. Les études réalisées ont souligné qu'il semble n'exister aucun remplacement sous-structural universel qui conserve toujours la bioactivité quel que soit le contexte biologique. Une généralisation des remplacements bioisostériques ne semble donc pas possible.

A Transportation Safety Planning Tool for the City of Ames, August 2011

The historically-reactive approach to identifying safety problems and mitigating them involves selecting black spots or hot spots by ranking locations based on crash frequency and severity. The approach focuses mainly on the corridor level without taking the exposure rate (vehicle miles traveled) and socio-demographics information of the study area, which are very important in the transportation planning process, into consideration. A larger study analysis unit at the Transportation Analysis Zone (TAZ) level or the network planning level should be used to address the needs of development of the community in the future and incorporate safety into the long-range transportation planning process. In this study, existing planning tools (such as the PLANSAFE models presented in NCHRP Report 546) were evaluated for forecasting safety in small and medium-sized communities, particularly as related to changes in socio-demographics characteristics, traffic demand, road network, and countermeasures. The research also evaluated the applicability of the Empirical Bayes (EB) method to network-level analysis. In addition, application of the United States Road Assessment Program (usRAP) protocols at the local urban road network level was investigated. This research evaluated the applicability of these three methods for the City of Ames, Iowa. The outcome of this research is a systematic process and framework for considering road safety issues explicitly in the small and medium-sized community transportation planning process and for quantifying the safety impacts of new developments and policy programs. More specifically, quantitative safety may be incorporated into the planning process, through effective visualization and increased awareness of safety issues (usRAP), the identification of high-risk locations with potential for improvement, (usRAP maps and EB), countermeasures for high-risk locations (EB before and after study and PLANSAFE), and socio-economic and demographic induced changes at the planning-level (PLANSAFE).

Cut-off importance sampling of bole volume

Summary

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

Uma análise do financiamento da educação no estado da Califórnia, EUA

Este trabalho é fruto de um estágio de pesquisa no Estado da Califórnia (EUA) e tem como objetivo analisar as principais características do financiamento da educação desse estado. A Califórnia possui 33 milhões de habitantes e cerca de seis milhões de alunos em seu sistema de educação básica que vai da pré-escola (kindergarten), em que as crianças entram com cinco anos de idade, até a 12ª série. O principal desafio enfrentado pelo estado, motivado principalmente por decisões judiciais, tem sido o de assegurar um patamar mínimo de recursos por aluno e o de evitar uma grande discrepância nos gastos por aluno entre distritos pobres e ricos. O que se constata é que o segundo objetivo tem sido parcialmente obtido mas basicamente mediante um nivelamento por baixo, de tal forma que o estado se coloca, hoje, em 40º lugar no ranking dos gastos por aluno no país.

Surface granularity as a discriminating feature of illicit tablets

In this paper we propose an innovative methodology for automated profiling of illicit tablets bytheir surface granularity; a feature previously unexamined for this purpose. We make use of the tinyinconsistencies at the tablet surface, referred to as speckles, to generate a quantitative granularity profileof tablets. Euclidian distance is used as a measurement of (dis)similarity between granularity profiles.The frequency of observed distances is then modelled by kernel density estimation in order to generalizethe observations and to calculate likelihood ratios (LRs). The resulting LRs are used to evaluate thepotential of granularity profiles to differentiate between same-batch and different-batches tablets.Furthermore, we use the LRs as a similarity metric to refine database queries. We are able to derivereliable LRs within a scope that represent the true evidential value of the granularity feature. Thesemetrics are used to refine candidate hit-lists form a database containing physical features of illicittablets. We observe improved or identical ranking of candidate tablets in 87.5% of cases when granularityis considered.

Expansão e qualidade da educação básica no Brasil

O trabalho consiste em uma apreciação crítica sobre a taxa de escolarização bruta, fluxo escolar, desempenho do estudante, evasão, repetência e outros indicadores utilizados como parâmetros para a avaliação da qualidade na educação básica brasileira. Trata-se de matéria de caráter ensaístico sobre o fato de que o custo de universalizar as matrículas foi uma perceptível queda no rendimento dos alunos. No entanto, o trabalho mostra que a qualidade deve ser considerada em termos representados pelos ganhos sociais da universalização do ensino e não unicamente pelas notas obtidas nas provas. São expostos problemas conceituais referentes ao novo Índice de Desenvolvimento da Educação Básica, utilizado na formulação de políticas públicas para que o Brasil melhore sua posição no ranking internacional da educação.

Phosphorus content of ditch sediments as indicator of critical source areas

Selostus : Kilpailukykyinen menetelmä pistemäisten fosforikuormitusalueiden paikantamiseen

Influence of weather, rank, and home advantage on football outcomes in the gulf region.

PURPOSE: The objective of this study was to investigate the effects of weather, rank, and home advantage on international football match results and scores in the Gulf Cooperation Council (GCC) region. METHODS: Football matches (n = 2008) in six GCC countries were analyzed. To determine the weather influence on the likelihood of favorable outcome and goal difference, generalized linear model with a logit link function and multiple regression analysis were performed. RESULTS: In the GCC region, home teams tend to have greater likelihood of a favorable outcome (P < 0.001) and higher goal difference (P < 0.001). Temperature difference was identified as a significant explanatory variable when used independently (P < 0.001) or after adjustment for home advantage and team ranking (P < 0.001). The likelihood of favorable outcome for GCC teams increases by 3% for every 1-unit increase in temperature difference. After inclusion of interaction with opposition, this advantage remains significant only when playing against non-GCC opponents. While home advantage increased the odds of favorable outcome (P < 0.001) and goal difference (P < 0.001) after inclusion of interaction term, the likelihood of favorable outcome for a GCC team decreased (P < 0.001) when playing against a stronger opponent. Finally, the temperature and wet bulb globe temperature approximation were found as better indicators of the effect of environmental conditions than absolute and relative humidity or heat index on match outcomes. CONCLUSIONS: In GCC region, higher temperature increased the likelihood of a favorable outcome when playing against non-GCC teams. However, international ranking should be considered because an opponent with a higher rank reduced, but did not eliminate, the likelihood of a favorable outcome.