888 resultados para analysis with NMR


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The first two articles build procedures to simulate vector of univariate states and estimate parameters in nonlinear and non Gaussian state space models. We propose state space speci fications that offer more flexibility in modeling dynamic relationship with latent variables. Our procedures are extension of the HESSIAN method of McCausland[2012]. Thus, they use approximation of the posterior density of the vector of states that allow to : simulate directly from the state vector posterior distribution, to simulate the states vector in one bloc and jointly with the vector of parameters, and to not allow data augmentation. These properties allow to build posterior simulators with very high relative numerical efficiency. Generic, they open a new path in nonlinear and non Gaussian state space analysis with limited contribution of the modeler. The third article is an essay in commodity market analysis. Private firms coexist with farmers' cooperatives in commodity markets in subsaharan african countries. The private firms have the biggest market share while some theoretical models predict they disappearance once confronted to farmers cooperatives. Elsewhere, some empirical studies and observations link cooperative incidence in a region with interpersonal trust, and thus to farmers trust toward cooperatives. We propose a model that sustain these empirical facts. A model where the cooperative reputation is a leading factor determining the market equilibrium of a price competition between a cooperative and a private firm

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A spectral angle based feature extraction method, Spectral Clustering Independent Component Analysis (SC-ICA), is proposed in this work to improve the brain tissue classification from Magnetic Resonance Images (MRI). SC-ICA provides equal priority to global and local features; thereby it tries to resolve the inefficiency of conventional approaches in abnormal tissue extraction. First, input multispectral MRI is divided into different clusters by a spectral distance based clustering. Then, Independent Component Analysis (ICA) is applied on the clustered data, in conjunction with Support Vector Machines (SVM) for brain tissue analysis. Normal and abnormal datasets, consisting of real and synthetic T1-weighted, T2-weighted and proton density/fluid-attenuated inversion recovery images, were used to evaluate the performance of the new method. Comparative analysis with ICA based SVM and other conventional classifiers established the stability and efficiency of SC-ICA based classification, especially in reproduction of small abnormalities. Clinical abnormal case analysis demonstrated it through the highest Tanimoto Index/accuracy values, 0.75/98.8%, observed against ICA based SVM results, 0.17/96.1%, for reproduced lesions. Experimental results recommend the proposed method as a promising approach in clinical and pathological studies of brain diseases

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Solid waste management nowadays is an important environmental issue in country like India. Statistics show that there has been substantial increase in the solid waste generation especially in the urban areas. This trend can be ascribed to rapid population growth, changing lifestyles, food habits, and change in living standards, lack of financial resources, institutional weaknesses, improper choice of technology and public apathy towards municipal solid waste. Waste is directly related to the consumption of resources and dumping to the land. Ecological footprint analysis – an impact assessment environment management tool makes a relationship between two factors- the amount of land required to dispose per capita generated waste. Ecological footprint analysis is a quantitative tool that represents the ecological load imposed on the earth by humans in spatial terms. By quantifying the ecological footprint we can formulate strategies to reduce the footprint and there by having a sustainable living. In this paper, an attempt is made to explore the tool Ecological Footprint Analysis with special emphasis to waste generation. The paper also discusses and analyses the waste footprint of Kochi city,India. An attempt is also made to suggest strategies to reduce the waste footprint thereby making the city sustainable, greener and cleaner

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The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).

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Mit dieser Arbeit wurde die Selbstassemblierung von dia- und paramagnetischen Molekülen sowie Einzelmolekülmagneten auf Goldsubstraten und magnetisch strukturierten Substraten untersucht. Dazu wurden drei verschiedene Klassen an Phthalocyaninderivaten verwendet: Diamagnetische Subphthalocyanine, paramagnetische Phthalocyaninatometalle und Diphthalocyaninatolanthanidkomplexe. Alle synthetisierten Verbindungen sind peripher thioethersubstituiert. Die Alkylketten (a: n-C8H17, b: n-C12H25) vermitteln die Löslichkeit in vielen organischen Solventien und sorgen für eine geordnete Assemblierung auf einer Oberfläche, wobei die Bindung auf Gold hauptsächlich über die Schwefelatome stattfindet. Die aus Lösung abgeschiedenen selbstassemblierten Monolagen wurden mit XPS, NEXAFS-Spektroskopie und ToF-SIMS untersucht. Bei der Selbstassemblierung auf magnetisch strukturierten Substraten stehen die Moleküle unter dem Einfluss magnetischer Streufelder und binden bevorzugt nur in bestimmten Bereichen. Die gebildeten Submonolagen wurden zusätzlich mit X-PEEM untersucht. Die erstmals dargestellten Manganphthalocyanine [MnClPc(SR)8] 1 wurden ausgehend von MnCl2 erhalten. Hier fand bei der Aufarbeitung an Luft eine Oxidation zu Mangan(III) statt; +III ist die stabilste Oxidationsstufe von Mangan in Phthalocyaninen. Der Nachweis des axialen Chloridoliganden erfolgte mit Massenspektrometrie und FIR- sowie Raman-Spektroskopie. SQUID-Messungen haben gezeigt, dass die Komplexe 1 vier ungepaarte Elektronen haben. Bei den Subphthalocyaninen [BClSubpc(SR)6] 2 wurde der axiale Chloridoligand mit dem stäbchenförmigen Phenolderivat 29-H substituiert und die erfolgreiche Ligandensubstitution durch NMR- und IR-Spektroskopie sowie Massenspektrometrie an den Produkten [BSubpc(SR)6(29)] 30 belegt. Der Radikalcharakter der synthetisierten Terbiumkomplexe [Tb{Pc(SR)8}2] 3 wurde spektroskopisch nachgewiesen; SQUID-Messungen ergaben, dass es sich um Einzelmolekülmagnete mit einer Energiebarriere U des Doppelpotentialtopfs von 880 K oder 610 cm-1 bei 3a handelt. Zunächst wurden die SAMs der Komplexverbindungen 1, 2, 30 und 3 auf nicht magnetisch strukturierten Goldsubstraten untersucht. Die Manganphthalocyanine 1 bilden geordnete SAMs mit größtenteils flach liegenden Molekülen, wie die XPS-, NEXAFS- und ToF-SIMS-Analyse zeigte. Die Mehrzahl der Thioether-Einheiten ist auf Gold koordiniert und die Alkylketten zeigen ungeordnet von der Oberfläche weg. Bei der Adsorption findet eine Reduktion zu Mangan(II) statt und der axiale Chloridoligand wird abgespalten. Das beruht auf dem sog. Oberflächen-trans-Effekt. Im vorliegenden Fall übt die Metalloberfläche einen stärkeren trans-Effekt als der axiale Ligand aus, was bisher experimentell noch nicht beobachtet wurde. Die thioethersubstituierten Subphthalocyanine 2 und 30 sowie die Diphthalocyaninatoterbium-Komplexe 3 sind ebenfalls für SAMs geeignet. Ihre Monolagen wurden mit XPS und NEXAFS-Spektroskopie untersucht, und trotz einer gewissen Unordnung in den Filmen liegen die Moleküle jeweils im Wesentlichen flach auf der Goldoberfläche. Vermutlich sind bei diesen Systemen auch die Alkylketten größtenteils parallel zur Oberfläche orientiert. Im Gegensatz zu den Manganphthalocyaninen 1 tritt bei 2b, 30a, 30b und 3b neben der koordinativen Bindung der Schwefelatome auf Gold auch eine für Thioether nicht erwartete kovalente Au–S-Bindung auf, die durch C–S-Bindungsbruch unter Abspaltung der Alkylketten ermöglicht wird. Der Anteil, zu dem dieser Prozess stattfindet, scheint nicht mit der Molekülstruktur zu korrelieren. Selbstassemblierte Submonolagen auf magnetisch strukturierten Substraten wurden mit dem diamagnetischen Subphthalocyanin 2b hergestellt. Der Nachweis der Submonolagen war schwierig und gelang schließlich durch eine Kombination von ToF-SIMS, NEXAFS Imaging und X-PEEM. Die Analyse der ToF-SIMS-Daten zeigte, dass tatsächlich eine Modulation der Verteilung der Moleküle auf einem unterwärts magnetisch strukturierten Substrat eintritt. Mit X-PEEM konnte die magnetische Struktur der ferromagnetischen Schicht des Substrats direkt der Verteilung der adsorbierten Moleküle zugeordnet werden. Die Subphthalocyanine 2b adsorbieren nicht an den Domänengrenzen, sondern vermehrt dazwischen. Auf Substraten mit abwechselnd 6.5 und 3.5 µm breiten magnetischen Domänen binden die Moleküle bevorzugt in den Bereichen geringster magnetischer Streufeldgradienten, also den größeren Domänen. Solche Substrate wurden für die ToF-SIMS- und X-PEEM-Messungen verwendet. Bei größeren magnetischen Strukturen mit ca. 400 µm breiten Domänen, wie sie aufgrund der geringeren Ortsauflösung dieser Methode für NEXAFS Imaging eingesetzt wurden, binden die Moleküle dann in allen Domänen. Die diamagnetischen Moleküle werden nach dieser Interpretation aus dem inhomogenen Magnetfeld über der Probenoberfläche heraus gedrängt und verhalten sich analog makroskopischer Diamagnete. Die eindeutige Detektion der Moleküle auf den magnetisch strukturierten Substraten konnte bisher nur für die diamagnetischen Subphthalocyanine 2b erfolgen. Um die Interpretation ihres Verhaltens bei der Selbstassemblierung in einem inhomogenen Magnetfeld weiter voranzutreiben, wurde das Subphthalocyanin 37b dargestellt, welches ein stabiles organisches TEMPO-Radikal in seinem axialen Liganden enthält. Das paramagnetische Subphthalocyanin 37b sollte auf den magnetisch strukturierten Substraten in Regionen starker magnetischer Streufelder binden und damit das entgegengesetzte Verhalten zu den diamagnetischen Subphthalocyaninen 2b zeigen. Aus Zeitgründen konnte dieser Nachweis im Rahmen dieser Arbeit noch nicht erbracht werden.

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To study the behaviour of beam-to-column composite connection more sophisticated finite element models is required, since component model has some severe limitations. In this research a generic finite element model for composite beam-to-column joint with welded connections is developed using current state of the art local modelling. Applying mechanically consistent scaling method, it can provide the constitutive relationship for a plane rectangular macro element with beam-type boundaries. Then, this defined macro element, which preserves local behaviour and allows for the transfer of five independent states between local and global models, can be implemented in high-accuracy frame analysis with the possibility of limit state checks. In order that macro element for scaling method can be used in practical manner, a generic geometry program as a new idea proposed in this study is also developed for this finite element model. With generic programming a set of global geometric variables can be input to generate a specific instance of the connection without much effort. The proposed finite element model generated by this generic programming is validated against testing results from University of Kaiserslautern. Finally, two illustrative examples for applying this macro element approach are presented. In the first example how to obtain the constitutive relationships of macro element is demonstrated. With certain assumptions for typical composite frame the constitutive relationships can be represented by bilinear laws for the macro bending and shear states that are then coupled by a two-dimensional surface law with yield and failure surfaces. In second example a scaling concept that combines sophisticated local models with a frame analysis using a macro element approach is presented as a practical application of this numerical model.

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In any discipline, where uncertainty and variability are present, it is important to have principles which are accepted as inviolate and which should therefore drive statistical modelling, statistical analysis of data and any inferences from such an analysis. Despite the fact that two such principles have existed over the last two decades and from these a sensible, meaningful methodology has been developed for the statistical analysis of compositional data, the application of inappropriate and/or meaningless methods persists in many areas of application. This paper identifies at least ten common fallacies and confusions in compositional data analysis with illustrative examples and provides readers with necessary, and hopefully sufficient, arguments to persuade the culprits why and how they should amend their ways

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Isotopic data are currently becoming an important source of information regarding sources, evolution and mixing processes of water in hydrogeologic systems. However, it is not clear how to treat with statistics the geochemical data and the isotopic data together. We propose to introduce the isotopic information as new parts, and apply compositional data analysis with the resulting increased composition. Results are equivalent to downscale the classical isotopic delta variables, because they are already relative (as needed in the compositional framework) and isotopic variations are almost always very small. This methodology is illustrated and tested with the study of the Llobregat River Basin (Barcelona, NE Spain), where it is shown that, though very small, isotopic variations comp lement geochemical principal components, and help in the better identification of pollution sources

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Many multivariate methods that are apparently distinct can be linked by introducing one or more parameters in their definition. Methods that can be linked in this way are correspondence analysis, unweighted or weighted logratio analysis (the latter also known as "spectral mapping"), nonsymmetric correspondence analysis, principal component analysis (with and without logarithmic transformation of the data) and multidimensional scaling. In this presentation I will show how several of these methods, which are frequently used in compositional data analysis, may be linked through parametrizations such as power transformations, linear transformations and convex linear combinations. Since the methods of interest here all lead to visual maps of data, a "movie" can be made where where the linking parameter is allowed to vary in small steps: the results are recalculated "frame by frame" and one can see the smooth change from one method to another. Several of these "movies" will be shown, giving a deeper insight into the similarities and differences between these methods

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We study a particular restitution problem where there is an indivisible good (land or property) over which two agents have rights: the dispossessed agent and the owner. A third party, possibly the government, seeks to resolve the situation by assigning rights to one and compensate the other. There is also a maximum amount of money available for the compensation. We characterize a family of asymmetrically fair rules that are immune to strategic behavior, guarantee minimal welfare levels for the agents, and satisfy the budget constraint.

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An improved method for the detection of pressed hazelnut oil in admixtures with virgin olive oil by analysis of polar components is described. The method. which is based on the SPE-based isolation of the polar fraction followed by RP-HPLC analysis with UV detection. is able to detect virgin olive oil adulterated with pressed hazelnut oil at levels as low as 5% with accuracy (90.0 +/- 4.2% recovery of internal standard), good reproducibility (4.7% RSD) and linearity (R-2: 0.9982 over the 5-40% adulteration range). An international ring-test of the developed method highlighted its capability as 80% of the samples were, on average, correctly identified despite the fact that no training samples were provided to the participating laboratories. However, the large variability in marker components among the pressed hazelnut oils examined prevents the use of the method for quantification of the level of adulteration. (C) 2003 Elsevier Ltd. All rights reserved.

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We explore the potential for making statistical decadal predictions of sea surface temperatures (SSTs) in a perfect model analysis, with a focus on the Atlantic basin. Various statistical methods (Lagged correlations, Linear Inverse Modelling and Constructed Analogue) are found to have significant skill in predicting the internal variability of Atlantic SSTs for up to a decade ahead in control integrations of two different global climate models (GCMs), namely HadCM3 and HadGEM1. Statistical methods which consider non-local information tend to perform best, but which is the most successful statistical method depends on the region considered, GCM data used and prediction lead time. However, the Constructed Analogue method tends to have the highest skill at longer lead times. Importantly, the regions of greatest prediction skill can be very different to regions identified as potentially predictable from variance explained arguments. This finding suggests that significant local decadal variability is not necessarily a prerequisite for skillful decadal predictions, and that the statistical methods are capturing some of the dynamics of low-frequency SST evolution. In particular, using data from HadGEM1, significant skill at lead times of 6–10 years is found in the tropical North Atlantic, a region with relatively little decadal variability compared to interannual variability. This skill appears to come from reconstructing the SSTs in the far north Atlantic, suggesting that the more northern latitudes are optimal for SST observations to improve predictions. We additionally explore whether adding sub-surface temperature data improves these decadal statistical predictions, and find that, again, it depends on the region, prediction lead time and GCM data used. Overall, we argue that the estimated prediction skill motivates the further development of statistical decadal predictions of SSTs as a benchmark for current and future GCM-based decadal climate predictions.

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We investigate the influence of articles, authors, journals and institutions in the field of environmental and ecological economics. We depart from studies that investigated the literature until 2001 and include a time period that has witnessed an enormous increase of importance in the field. We adjust for the age effect given the huge impact of the year of an article's publication on its influence and we show that this adjustment does make a substantial difference — especially for disaggregated units of analysis with diverse age characteristics such as articles or authors. We analyse 6597 studies on environmental and ecological economics published between 2000 and 2009. We provide rankings of the influential articles, authors, journals and institutions and find that Ecological Economics, Energy Economics and the Journal of Environmental Economics and Management have the most influential articles, they publish very influential authors and their articles are cited most. The University of Maryland, Resources for the Future, the University of East Anglia and the World Bank appear to be the most influential institutions in the field of environmental and ecological economics.

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This thesis is concerned with development of improved management practices in indigenous chicken production systems in a research process that includes participatory approaches with smallholder farmers and other stakeholders in Kenya. The research process involved a wide range of activities that included on-station experiments, field surveys, stakeholder consultations in workshops, seminars and visits, and on-farm farmer participatory research to evaluate the effect of some improved management interventions on production performance of indigenous chickens. The participatory research was greatly informed from collective experiences and lessons of the previous activities. The on-station studies focused on hatching, growth and nutritional characteristics of the indigenous chickens. Four research publications from these studies are included in this thesis. Quantitative statistical analyses were applied and they involved use of growth models estimated with non-linear regressions for the growth characteristics, chi-square determinations to investigate differences among different reciprocal crosses of indigenous chickens and general linear models and covariance determination for the nutrition study. The on-station studies brought greater understanding of performance and production characteristics of indigenous chickens and the influence of management practices on these characteristics. The field surveys and stakeholder consultations helped in understanding the overarching issues affecting the productivity of the indigenous chickens systems and their place in the livelihoods of smallholder farmers. These activities created strong networking opportunities with stakeholders from a wide spectrum. The on-farm farmer participatory research involved selection of 200 farmers in five regions followed by training and introduction of interventions on improved management practices which included housing, vaccination, deworming and feed supplementation. Implementation and monitoring was mainly done by individual farmers continuously for close to one and half years. Six quarterly visits to the farms were made by the research team to monitor and provide support for on-going project activities. The data collected has been analysed for 5 consecutive 3-monthly periods. Descriptive and inferential statistics were applied to analyse the data collected involving treatment applications, production characteristics and flock demography characteristics. Out of the 200 farmers initially selected, 173 had records on treatment applications and flock demography characteristics while 127 farmers had records on production characteristics. The demographic analysis with a dissimilarity index of flock size produced 7 distinct farm groups from among the 173 farms. Two of these farm groups were represented in similar numbers in each of the five regions. The research process also involved a number of dissemination and communication strategies that have brought the process and project outcomes into the domain of accessibility by wider readership locally and globally. These include workshops, seminars, field visits and consultations, local and international conferences, electronic conferencing, publications and personal communication via emailing and conventional posting. A number of research and development proposals were also developed based on the knowledge and experiences gained from the research process. The thesis captures the research process activities and outcomes in 8 chapters which include in ascending order – introduction, theoretical concepts underpinning FPR, research methodology and process, on-station research output, FPR descriptive statistical analysis, FPR inferential statistical analysis on production characteristics, FPR demographic analysis and conclusions. Various research approaches both quantitative and qualitative have been applied in the research process indicating the possibilities and importance of combining both systems for greater understanding of issues being studied. In our case, participatory studies of the improved management of indigenous chickens indicates their potential importance as livelihood assets for poor people.

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We investigate the influence of articles, authors, journals and institutions in the field of environmental and ecological economics. We depart from studies that investigated the literature until 2001 and include a time period that has witnessed an enormous increase of importance in the field. We adjust for the age effect given the huge impact of the year of an article's publication on its influence and we show that this adjustment does make a substantial difference — especially for disaggregated units of analysis with diverse age characteristics such as articles or authors. We analyse 6597 studies on environmental and ecological economics published between 2000 and 2009. We provide rankings of the influential articles, authors, journals and institutions and find that Ecological Economics, Energy Economics and the Journal of Environmental Economics and Management have the most influential articles, they publish very influential authors and their articles are cited most. The University of Maryland, Resources for the Future, the University of East Anglia and the World Bank appear to be the most influential institutions in the field of environmental and ecological economics.