Fusarium head blight evaluation and genetic stability in synthetic hexaploid wheats.

2016

Forage peanut (Arachis spp.) genetic evaluation and selection.

Forage peanut improvement for use in grass?legume mixtures is expected to have a great impact on the sustainability of Brazilian livestock production. Eighteen cloned Arachis spp. ecotypes were evaluated under clipping in a Brazilian Cerrado region and results analysed using a mixed model methodology. The objective was to estimate genetic and phenotypic parameters and to select the best ecotypes based on selection index applied on their predicted genotypic value. The traits of total dry-matter (DM) and leaf DM yield presented moderate (0_30 < h2g < 0_50) to high (>0_50) broad-sense heritability, in contrast to the low genetic variability in nutritional quality-associated traits. Ecotypes of Arachis spp. contained average crude protein concentrations of 224 g kg _1 DM in leaves and 138 g kg _1 DM in stems, supporting the potential role of these species to overcome the low protein content in Cerrado pastures. The correlations between yield traits and traits associated with low nutritional value in leaves were consistently significant and positive. Genetic correlations among all the yield traits evaluated during the rainy or dry seasons were significant and positive. The ecotypes were ranked based on selection index. The next step is to validate long-term selection of grass?Arachis in combination with pastures under competition and adjusted grazing in the Cerrado region.

Computational immunology: The coming of age

The explosive growth in biotechnology combined with major advancesin information technology has the potential to radically transformimmunology in the postgenomics era. Not only do we now have readyaccess to vast quantities of existing data, but new data with relevanceto immunology are being accumulated at an exponential rate. Resourcesfor computational immunology include biological databases and methodsfor data extraction, comparison, analysis and interpretation. Publiclyaccessible biological databases of relevance to immunologists numberin the hundreds and are growing daily. The ability to efficientlyextract and analyse information from these databases is vital forefficient immunology research. Most importantly, a new generationof computational immunology tools enables modelling of peptide transportby the transporter associated with antigen processing (TAP), modellingof antibody binding sites, identification of allergenic motifs andmodelling of T-cell receptor serial triggering.

Pubalgia num atleta de futebol: estudo de caso

Introdução: No fu tebol os atletas são submetidos a um grande número de treinos e jogos, não havendo muitas vezes tempo necessário para o repouso ou alongamentos, estes factores predispõem o aparecimento de lesões incapacitantes como a pubalgia. O fisioterapeuta deverá realizar uma correcta avaliação e interpretação dos sintomas e das alterações posturais e biomecânicas do paciente com pubalgia. Objectivo: Através deste estudo de caso pretende-se descrever a avaliação e intervenção num caso de um jogador de fu tebol com pubalgia, salientando o processo de raciocínio clín ico desenvolvido ao longo do tratamento. Intervenção: Após a avaliação inicial, foi estabelecido, em conjunto com o atleta, um plano de tratamento por um períodlo de cinco semanas com três sessões semanais e exercícios durante os restantes dias. A intervenção visou a diminuição da dor, normalização das alterações articu lares, reforço da musculatu ra enfraquecida, promoção da estabilidade lombopélvica, restabelecimento da mobilidade das cadeias musculares encurtadas e retorno à actividade desportiva. Resultados: Verificou-se uma diminuição da dor, associada a um aumento de flexibilidade e de força. Conclusão: Através da abordagem pelo conceito de cadeias lesionais associado ao tratamento global de fisioterapia (exercícios terapêuticos, electroterapia, massagem), obteve-se melhorias clinicamente importantes num período de cinco semanas, verificando-se no fim do tratamento a ausência de sintomatologia, o que permitiu o retorno do atleta à actividade desportiva.

Design gráfico da pluma de contaminação por compostos orgânicos voláteiss utilizando software CAD na investigação de passivo ambiental em um posto revendedor de combustíveis em Natal/RN

Among the potentially polluting economic activities that compromise the quality of groundwater are the gas stations. The city of Natal has about 120 gas stations, of which only has an environmental license for operation. Discontinuities in the offices were notified by the Public Ministry of Rio Grande do Norte to carry out the environmental adaptations, among which is the investigation of environmental liabilities. The preliminary and confirmatory stages of this investigation consisted in the evaluation of soil gas surveys with two confirmatory chemical analysis of BTEX, PAH and TPH. To get a good evaluation and interpretation of results obtained in the field, it became necessary three-dimensional representation of them. We used a CAD software to graph the equipment installed in a retail service station fuel in Natal, as well as the plumes of contamination by volatile organic compounds. The tool was concluded that contamination is not located in the current system of underground storage of fuel development, but reflects the historical past in which tanks were removed not tight gasoline and diesel

Planktological-chemical observation during the International Indian Ocean Expedition (IIOE) with RV "Meteor" in 1964/65

The present volume contains the planktological data collected during the expedition of the "Meteor" to the Indian Ocean in 1964/65. It was the main objective of the expedition to study the up- and downwelling conditioned along the western and eastern coasts of the Arabian Sea by the northeastern monsoon. It is from these areas that the greater part of the data here presented was obtained. A few values from the Red Sea have been added. As the title "Planktological-Chemical Data" implies, it was chiefly with the help of chemical methods that the planktological investigations, with the exception of the particle size analysis and phytoplankton counting conducted optically, were carried out. These investigations were above all devoted to a quantitative survey of particulate matter and plankton, the latter being sampled by water-bottle and net. The zooplankton hauls were taken with the Indian Ocean Standard Net according to the international guidelines laid down for the expedition. As a rule, double catches were made at every station, one sample being intended for laboratory analysis at the Indian Ocean Biological Centre in Ernakulam, South India, and the other for the Institut für Meereskunde in Kiel. In addition to determining the standing stock, the production rate of phytoplankton was measured by the 14C method. These experiments were mainly conducted during the latter half of the expedition. The planktological studies primarily covered the euphotic zone, extending into the underlying water layers up to a depth of 600 m. The investigations were above all directed towards ascertaining the quantity of organic substance, formed by primary production, in its relation to environmental conditions and determining whether or not organic substance is actively transported from the surface into the deeper layers by the periodically migration organisms of the deep scattering layers. Depending on the station time available, a few samples could now and then be taken from deeper layers. The present volume of planktological-chemical data addresses itself to all those concerned processing the extensive material collected during the International Indian Ocean Expedition. As a readily accessible work of reference, it hopes to serve as an aid in the evaluation and interpretation of the expedition results. The complementary ecological data such as temperature, salinity, and oxygen content as well as the figures obtained on abundance and distribution in depth of the nutrients essential for primary production may be found in the volume of physical-chemical data published in Series A of the "Meteor"-Forschungsergebnisse No. 2, 1966 (Dietrich et al., 1966).

Zonas de actividad logística : 25 años de experiencia española : evolución y tendencias : criterios y parámetros de diseño para su implantación y ordenación

El objeto de la investigación es analizar la situación de las plataformas logísticas y caracterizar las mismas, sus áreas funcionales y los parámetros de diseño que se utilizan para su planificación y desarrollo. La investigación se ha realizado sobre las plataformas logísticas existentes en España, si bien se ha contrastado la situación nacional con otras experiencias internacionales. Para ello se ha procedido al estudio del estado del arte a nivel internacional, determinando la terminología, caracterización y clasificación que aporta la comunidad científica al respecto sobre las plataformas logísticas. La investigación se ha centrado en el estudio de un elevado número de plataformas logísticas ubicadas en distintas Comunidades Autónomas, que representan en torno al cuarenta por ciento de las que se encuentran en estos momentos en activo, analizando sus datos básicos, su clasificación en lo que respecta a su grado de centralidad, su intermodalidad, su accesibilidad, y la información urbanística relativa a superficies de áreas funcionales, edificabilidades, usos principales, complementarios y no admitidos, red viaria, zonas verdes, y parámetros máximos y mínimos de ordenación. El análisis, valoración e interpretación de los resultados obtenidos, ha permitido concluir en la heterogeneidad existente sobre el término, proponiéndose por parte del autor un nuevo concepto que englobe y defina de forma genérica pero clara la tipología de plataformas logísticas presentes en el panorama nacional. Del mismo modo, y como consecuencia de la investigación realizada, ha sido posible la caracterización de una “plataforma logística tipo”, estableciendo unos parámetros de diseño estándar para desarrollos posteriores. Finalmente se proponen varias líneas de investigación. En primer lugar, analizar el conjunto del transporte de mercancías, para determinar y valorar su desequilibrio, para de este modo potenciar la intermodalidad e internacionalizar la misma; y, en segundo lugar, establecer una regulación global de las competencias y legislación en materia de planificación de centros logísticos, para racionalizar el desarrollo de estos elementos. The aim of this research is to analyze the situation of logistics platforms and to characterize them, their functional areas and the design parameters that are used in their planning and development. This study was conducted on logistics platforms in Spain, although the situation in Spain has been compared to other international experiences. For this purpose, the international state-of-the-art has been examined, determining the terminology, characterization and classification provided by the scientific community in regard to logistics platforms. The research focuses on the study of a large number of logistics platforms located in different Autonomous Regions, representing approximately 40% of those currently in operation. An analysis has been made of the fundamental data, classification in regard to the degree of centrality, intermodality, accessibility and the urban planning information relating to functional area spaces, as well as buildable potential, main, complementary and prohibited uses, the road network, green zones and maximum and minimum development planning parameters. The analysis, evaluation and interpretation of the results obtained has led to the conclusion of the heterogeneous nature of the term, and the author proposes a new concept that would cover and define, in a generic yet clear way, the typology of logistics platforms present in the national scenario. In a similar manner, and as a result of the research conducted, it has been possible to define a “logistics platform type”, establishing standard design parameters for future developments. Lastly, various lines of research are proposed. In the first place, to analyze overall goods transport to determine and evaluate its imbalances and, in this way, to promote its intermodality and internationalization. In the second place, to establish a global regulation of competencies and legislation with regard to the planning of logistics centers, to rationalize the development of these elements.

Koherentziazko diskurtso erlazioen detekzio automatikoa patroien bidez, XMLko erlazio-egiturak oinarri hartuta

[EU]Hizkuntzaren prozesamenduan testu koherenteetan kausa taldeko erlazioak (KAUSA, ONDORIOA eta HELBURUA) automatikoki hautematea eta bereiztea erabilgarria da galdera-erantzun automatikoko sistemak eraikitzerako orduan. Horretarako Egitura Erretorikoaren Teoria (Rhetorical Structure Theory, aurrerantzean RST) eta bere erlazioak erabiliko ditugu, corpus bezala RST Treebank -a (Iruskieta et al., 2013) hartuta, zientziako laburpen-testuz osatutako corpusa, hain zuzen ere. Corpus hori XML formatuan deskargatu eta hortik XPATH tresnaren bidez informazio garrantzitsuena eskuratzen dugu. Lan honek 3 helburu nagusi ditu: lehendabizi, kausa taldeko erlazioak elkarren artean bereiztea, bigarrenez, kausa taldeko erlazio hauek beste erlazio guztiekin bereiztea, eta azkenik, EBALUAZIOA eta INTERPRETAZIOA erlazioak bereiztea sentimendu analisian aplikatu ahal izateko. Ataza horiek egiteko, RhetDB tresnarekin eskuratu diren patroi ensaguratsuenak erabili eta bi aplikazio garatu ditugu. Alde batetik, bilatu nahi ditugun patroiak adierazi eta erlazio-egitura duen edonolako testuetan bilaketak egiten dituen bilatzailea, eta bestetik, patroi esanguratsuenak emanda erlazioak etiketatzen dituen etiketatzailea. Bi aplikazio hauek gainera, ahalik eta modu parametrizagarrienean erabiltzeko garatu ditugu, kodea aldatu gabe edonork erabili ahal izateko antzeko atazak egiteko. Etiketatzaileak ebaluatu ondoren, identifikatzeko erlaziorik errazena HELBURUA erlazioa dela ikusi dugu eta KAUSA eta ONDORIOA bereizteko arazo gehiago dauzkagula ere ondorioztatu dugu. Modu berean, EBALUAZIOA eta INTERPRETAZIOA ere elkarren artean bereiz dezakegula ikusi dugu.

Design gráfico da pluma de contaminação por compostos orgânicos voláteiss utilizando software CAD na investigação de passivo ambiental em um posto revendedor de combustíveis em Natal/RN

Among the potentially polluting economic activities that compromise the quality of groundwater are the gas stations. The city of Natal has about 120 gas stations, of which only has an environmental license for operation. Discontinuities in the offices were notified by the Public Ministry of Rio Grande do Norte to carry out the environmental adaptations, among which is the investigation of environmental liabilities. The preliminary and confirmatory stages of this investigation consisted in the evaluation of soil gas surveys with two confirmatory chemical analysis of BTEX, PAH and TPH. To get a good evaluation and interpretation of results obtained in the field, it became necessary three-dimensional representation of them. We used a CAD software to graph the equipment installed in a retail service station fuel in Natal, as well as the plumes of contamination by volatile organic compounds. The tool was concluded that contamination is not located in the current system of underground storage of fuel development, but reflects the historical past in which tanks were removed not tight gasoline and diesel

Comparison of gadoteric acid and gadobutrol for detection as well as morphologic and dynamic characterization of lesions on breast dynamic contrast-enhanced magnetic resonance imaging

OBJECTIVE In contrast to conventional breast imaging techniques, one major diagnostic benefit of breast magnetic resonance imaging (MRI) is the simultaneous acquisition of morphologic and dynamic enhancement characteristics, which are based on angiogenesis and therefore provide insights into tumor pathophysiology. The aim of this investigation was to intraindividually compare 2 macrocyclic MRI contrast agents, with low risk for nephrogenic systemic fibrosis, in the morphologic and dynamic characterization of histologically verified mass breast lesions, analyzed by blinded human evaluation and a fully automatic computer-assisted diagnosis (CAD) technique. MATERIALS AND METHODS Institutional review board approval and patient informed consent were obtained. In this prospective, single-center study, 45 women with 51 histopathologically verified (41 malignant, 10 benign) mass lesions underwent 2 identical examinations at 1.5 T (mean time interval, 2.1 days) with 0.1-mmol kg doses of gadoteric acid and gadobutrol. All magnetic resonance images were visually evaluated by 2 experienced, blinded breast radiologists in consensus and by an automatic CAD system, whereas the morphologic and dynamic characterization as well as the final human classification of lesions were performed based on the categories of the Breast imaging reporting and data system MRI atlas. Lesions were also classified by defining their probability of malignancy (morpho-dynamic index; 0%-100%) by the CAD system. Imaging results were correlated with histopathology as gold standard. RESULTS The CAD system coded 49 of 51 lesions with gadoteric acid and gadobutrol (detection rate, 96.1%); initial signal increase was significantly higher for gadobutrol than for gadoteric acid for all and the malignant coded lesions (P < 0.05). Gadoteric acid resulted in more postinitial washout curves and fewer continuous increases of all and the malignant lesions compared with gadobutrol (CAD hot spot regions, P < 0.05). Morphologically, the margins of the malignancies were different between the 2 agents, whereas gadobutrol demonstrated more spiculated and fewer smooth margins (P < 0.05). Lesion classifications by the human observers and by the morpho-dynamic index compared with the histopathologic results did not significantly differ between gadoteric acid and gadobutrol. CONCLUSIONS Macrocyclic contrast media can be reliably used for breast dynamic contrast-enhanced MRI. However, gadoteric acid and gadobutrol differed in some dynamic and morphologic characterization of histologically verified breast lesions in an intraindividual, comparison. Besides the standardization of technical parameters and imaging evaluation of breast MRI, the standardization of the applied contrast medium seems to be important to receive best comparable MRI interpretation.

Spatial and temporal variation in distribution of mangroves in Moreton Bay, subtropical Australia: a comparison of pattern metrics and change detection analyses based on aerial photographs

An assessment of the changes in the distribution and extent of mangroves within Moreton Bay, southeast Queensland, Australia, was carried out. Two assessment methods were evaluated: spatial and temporal pattern metrics analysis, and change detection analysis. Currently, about 15,000 ha of mangroves are present in Moreton Bay. These mangroves are important ecosystems, but are subject to disturbance from a number of sources. Over the past 25 years, there has been a loss of more than 3800 ha, as a result of natural losses and mangrove clearing (e.g. for urban and industrial development, agriculture and aquaculture). However, areas of new mangroves have become established over the same time period, offsetting these losses to create a net loss of about 200 ha. These new mangroves have mainly appeared in the southern bay region and the bay islands, particularly on the landward edge of existing mangroves. In addition, spatial patterns and species composition of mangrove patches have changed. The pattern metrics analysis provided an overview of mangrove distribution and change in the form of single metric values, while the change detection analysis gave a more detailed and spatially explicit description of change. An analysis of the effects of spatial scales on the pattern metrics indicated that they were relatively insensitive to scale at spatial resolutions less than 50 m, but that most metrics became sensitive at coarser resolutions, a finding which has implications for mapping of mangroves based on remotely sensed data. (C) 2003 Elsevier Science B.V. All rights reserved.

Cephalometric evaluation of facial pattern and hyoid bone position in children with obstructive sleep apnea syndrome

Objectives: To assess the development of face and hyoid bone in children with obstructive sleep apnea syndrome (OSAS) through lateral cephalometries. Materials and methods: Children aged 7-10 years with mixed dentition and with no previous otorhinolaryngologic, orthodontic or speech therapy treatments were studied. Twenty nasal breathers were compared to 20 mouth breathing children diagnosed as OSAS patients. All children underwent otorhinolaryngologic evaluation and cephalometries; children with OSAS also underwent nocturnal polysomnography in a sleep laboratory. Results: Children with OSAS presented increase in total and lower anterior heights of the face when compared to nasal breathers. In addition, children with OSAS presented a significantly more anterior and inferior position of the hyoid bone than nasal breathers. No significant differences in upper, anterior or posterior heights of the face were observed between groups. Conclusion: The results suggest that there are evident and early changes in facial growth and development among children with OSAS, characterized by increased total and inferior anterior heights of the face, as well as more anterior and inferior position of the hyoid bone. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Economic evaluation of proposed pure and mixed stands in Central Vietnam highlands

In comparison with mixed forest stands, the cultivation of pure plantations in Vietnam entails serious ecological consequences such as loss of biodiversity and higher rate of soil erosion. The economic evaluation is elaborated between pure plantations and mixed forests where the fast-growing tree species are mixed with slow growing tree species which are planted in stripes separating the segments with fast-growing tree species (Acacia sp.). For the evaluation, the input values were used from local costs of goods, services and labour. The results show that the internal rate of return is the highest in the case of pure plantation in comparison with mixed forests – 86% to 77%(first planting pattern: Acacia sp. + noble hardwood species) and 54% (second planting pattern: Acacia + Dipterocarpus sp. + Sindora sp.). The average profit per hectare and year is almost five times higher in the case of mixed stands. The first planting pattern reaches 2,650 $, the second planting pattern 2,280 $ and the pure acacia plantation only 460 $. From an economic point of view, the cultivation of mixed forests that corresponds to the principles of sustainable forestry generates a good economical profit while maintaining habitat complexity and biodiversity.

Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets

Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.