Analysis of the impact of rainfall assimilation during LBA atmospheric mesoscale missions in Southwest Amazon

The assimilation of satellite estimated precipitation data can be used as an efficient tool to improve the analysis of rainfall generated by numerical models of weather forecast. The system of data assimilation used in this study is cumulus parameterization inversion based on the Kuo scheme. Reanalysis were performed using the field experiment data of the LBA Project (WETAMC and DRYtoWET-AMC), where it was possible to verify an improvement in the simulations results, since the data assimilation corrects the position and the intensity of rainfall in the numerical model. (C) 2012 Elsevier B.V. All rights reserved.

The use of parthenotegenetic and IVF bovine blastocysts as a model for the creation of human embryonic stem cells under defined conditions

Clinical application of human embryonic stem cells will be possible, when cell lines are created under xeno-free and defined conditions. We aimed to establish methodologies for parthenogenetic activation, culture to blastocyst and mechanical isolation of the inner cell mass (ICM) using bovine oocytes, as a model for derivation and proliferation of human embryonic stem cells under defined xeno-free culture conditions. Cumulus-oocyte-complexes were in vitro matured and activated using Ca(2+)Ionophore and 6-DMAP or in vitro fertilized (IVF). Parthenotes and biparental embryos were cultured to blastocysts, when their ICM was mechanically isolated and placed onto a substrate of fibronectin in StemProA (R) medium. After attachment, primary colonies were left to proliferate and stained for pluripotency markers, alkaline phosphatase and Oct-4. Parthenogenesis and fertilization presented significantly different success rates (91 and 79 %, respectively) and blastocyst formation (40 and 43 %, respectively). ICMs from parthenogenetic and IVF embryos formed primary and expanded colonies at similar rates (39 % and 33 %, respectively). Six out of eight parthenogenetic colonies tested positive for alkaline phosphatase. Three colonies were analyzed for Oct-4 and they all tested positive for this pluripotency marker. Our data show that Ca2+ Ionophore, and 6-DMAP are efficient in creating large numbers of blastocysts to be employed as a model for human oocyte activation and embryo development. After mechanical isolation, parthenogetic derived ICMs showed a good rate of derivation in fibronectin and Stem-Pro forming primary and expanded colonies of putative embryonic stem cells. This methodology may be a good strategy for parthenogenetic activation of discarded human oocytes and derivation in defined conditions for future therapeutic interventions.

Essays on the political economy of European integration

Recently, a rising interest in political and economic integration/disintegration issues has been developed in the political economy field. This growing strand of literature partly draws on traditional issues of fiscal federalism and optimum public good provision and focuses on a trade-off between the benefits of centralization, arising from economies of scale or externalities, and the costs of harmonizing policies as a consequence of the increased heterogeneity of individual preferences in an international union or in a country composed of at least two regions. This thesis stems from this strand of literature and aims to shed some light on two highly relevant aspects of the political economy of European integration. The first concerns the role of public opinion in the integration process; more precisely, how economic benefits and costs of integration shape citizens' support for European Union (EU) membership. The second is the allocation of policy competences among different levels of government: European, national and regional. Chapter 1 introduces the topics developed in this thesis by reviewing the main recent theoretical developments in the political economy analysis of integration processes. It is structured as follows. First, it briefly surveys a few relevant articles on economic theories of integration and disintegration processes (Alesina and Spolaore 1997, Bolton and Roland 1997, Alesina et al. 2000, Casella and Feinstein 2002) and discusses their relevance for the study of the impact of economic benefits and costs on public opinion attitude towards the EU. Subsequently, it explores the links existing between such political economy literature and theories of fiscal federalism, especially with regard to normative considerations concerning the optimal allocation of competences in a union. Chapter 2 firstly proposes a model of citizens’ support for membership of international unions, with explicit reference to the EU; subsequently it tests the model on a panel of EU countries. What are the factors that influence public opinion support for the European Union (EU)? In international relations theory, the idea that citizens' support for the EU depends on material benefits deriving from integration, i.e. whether European integration makes individuals economically better off (utilitarian support), has been common since the 1970s, but has never been the subject of a formal treatment (Hix 2005). A small number of studies in the 1990s have investigated econometrically the link between national economic performance and mass support for European integration (Eichenberg and Dalton 1993; Anderson and Kalthenthaler 1996), but only making informal assumptions. The main aim of Chapter 2 is thus to propose and test our model with a view to providing a more complete and theoretically grounded picture of public support for the EU. Following theories of utilitarian support, we assume that citizens are in favour of membership if they receive economic benefits from it. To develop this idea, we propose a simple political economic model drawing on the recent economic literature on integration and disintegration processes. The basic element is the existence of a trade-off between the benefits of centralisation and the costs of harmonising policies in presence of heterogeneous preferences among countries. The approach we follow is that of the recent literature on the political economy of international unions and the unification or break-up of nations (Bolton and Roland 1997, Alesina and Wacziarg 1999, Alesina et al. 2001, 2005a, to mention only the relevant). The general perspective is that unification provides returns to scale in the provision of public goods, but reduces each member state’s ability to determine its most favoured bundle of public goods. In the simple model presented in Chapter 2, support for membership of the union is increasing in the union’s average income and in the loss of efficiency stemming from being outside the union, and decreasing in a country’s average income, while increasing heterogeneity of preferences among countries points to a reduced scope of the union. Afterwards we empirically test the model with data on the EU; more precisely, we perform an econometric analysis employing a panel of member countries over time. The second part of Chapter 2 thus tries to answer the following question: does public opinion support for the EU really depend on economic factors? The findings are broadly consistent with our theoretical expectations: the conditions of the national economy, differences in income among member states and heterogeneity of preferences shape citizens’ attitude towards their country’s membership of the EU. Consequently, this analysis offers some interesting policy implications for the present debate about ratification of the European Constitution and, more generally, about how the EU could act in order to gain more support from the European public. Citizens in many member states are called to express their opinion in national referenda, which may well end up in rejection of the Constitution, as recently happened in France and the Netherlands, triggering a European-wide political crisis. These events show that nowadays understanding public attitude towards the EU is not only of academic interest, but has a strong relevance for policy-making too. Chapter 3 empirically investigates the link between European integration and regional autonomy in Italy. Over the last few decades, the double tendency towards supranationalism and regional autonomy, which has characterised some European States, has taken a very interesting form in this country, because Italy, besides being one of the founding members of the EU, also implemented a process of decentralisation during the 1970s, further strengthened by a constitutional reform in 2001. Moreover, the issue of the allocation of competences among the EU, the Member States and the regions is now especially topical. The process leading to the drafting of European Constitution (even if then it has not come into force) has attracted much attention from a constitutional political economy perspective both on a normative and positive point of view (Breuss and Eller 2004, Mueller 2005). The Italian parliament has recently passed a new thorough constitutional reform, still to be approved by citizens in a referendum, which includes, among other things, the so called “devolution”, i.e. granting the regions exclusive competence in public health care, education and local police. Following and extending the methodology proposed in a recent influential article by Alesina et al. (2005b), which only concentrated on the EU activity (treaties, legislation, and European Court of Justice’s rulings), we develop a set of quantitative indicators measuring the intensity of the legislative activity of the Italian State, the EU and the Italian regions from 1973 to 2005 in a large number of policy categories. By doing so, we seek to answer the following broad questions. Are European and regional legislations substitutes for state laws? To what extent are the competences attributed by the European treaties or the Italian Constitution actually exerted in the various policy areas? Is their exertion consistent with the normative recommendations from the economic literature about their optimum allocation among different levels of government? The main results show that, first, there seems to be a certain substitutability between EU and national legislations (even if not a very strong one), but not between regional and national ones. Second, the EU concentrates its legislative activity mainly in international trade and agriculture, whilst social policy is where the regions and the State (which is also the main actor in foreign policy) are more active. Third, at least two levels of government (in some cases all of them) are significantly involved in the legislative activity in many sectors, even where the rationale for that is, at best, very questionable, indicating that they actually share a larger number of policy tasks than that suggested by the economic theory. It appears therefore that an excessive number of competences are actually shared among different levels of government. From an economic perspective, it may well be recommended that some competences be shared, but only when the balance between scale or spillover effects and heterogeneity of preferences suggests so. When, on the contrary, too many levels of government are involved in a certain policy area, the distinction between their different responsibilities easily becomes unnecessarily blurred. This may not only leads to a slower and inefficient policy-making process, but also risks to make it too complicate to understand for citizens, who, on the contrary, should be able to know who is really responsible for a certain policy when they vote in national,local or European elections or in referenda on national or European constitutional issues.

Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

Role of BDNF secretion and signaling in the activity-dependent refinement of synaptic connections

Neuronal networks exhibit diverse types of plasticity, including the activity-dependent regulation of synaptic functions and refinement of synaptic connections. In addition, continuous generation of new neurons in the “adult” brain (adult neurogenesis) represents a powerful form of structural plasticity establishing new connections and possibly implementing pre-existing neuronal circuits (Kempermann et al, 2000; Ming and Song, 2005). Neurotrophins, a family of neuronal growth factors, are crucially involved in the modulation of activity-dependent neuronal plasticity. The first evidence for the physiological importance of this role evolved from the observations that the local administration of neurotrophins has dramatic effects on the activity-dependent refinement of synaptic connections in the visual cortex (McAllister et al, 1999; Berardi et al, 2000; Thoenen, 1995). Moreover, the local availability of critical amounts of neurotrophins appears to be relevant for the ability of hippocampal neurons to undergo long-term potentiation (LTP) of the synaptic transmission (Lu, 2004; Aicardi et al, 2004). To achieve a comprehensive understanding of the modulatory role of neurotrophins in integrated neuronal systems, informations on the mechanisms about local neurotrophins synthesis and secretion as well as ditribution of their cognate receptors are of crucial importance. In the first part of this doctoral thesis I have used electrophysiological approaches and real-time imaging tecniques to investigate additional features about the regulation of neurotrophins secretion, namely the capability of the neurotrophin brain-derived neurotrophic factor (BDNF) to undergo synaptic recycling. In cortical and hippocampal slices as well as in dissociated cell cultures, neuronal activity rapidly enhances the neuronal expression and secretion of BDNF which is subsequently taken up by neurons themselves but also by perineuronal astrocytes, through the selective activation of BDNF receptors. Moreover, internalized BDNF becomes part of the releasable source of the neurotrophin, which is promptly recruited for activity-dependent recycling. Thus, we described for the first time that neurons and astrocytes contain an endocytic compartment competent for BDNF recycling, suggesting a specialized form of bidirectional communication between neurons and glia. The mechanism of BDNF recycling is reminiscent of that for neurotransmitters and identifies BDNF as a new modulator implicated in neuro- and glio-transmission. In the second part of this doctoral thesis I addressed the role of BDNF signaling in adult hippocampal neurogenesis. I have generated a transgenic mouse model to specifically investigate the influence of BDNF signaling on the generation, differentiation, survival and connectivity of newborn neurons into the adult hippocampal network. I demonstrated that the survival of newborn neurons critically depends on the activation of the BDNF receptor TrkB. The TrkB-dependent decision regarding life or death in these newborn neurons takes place right at the transition point of their morphological and functional maturation Before newborn neurons start to die, they exhibit a drastic reduction in dendritic complexity and spine density compared to wild-type newborn neurons, indicating that this receptor is required for the connectivity of newborn neurons. Both the failure to become integrated and subsequent dying lead to impaired LTP. Finally, mice lacking a functional TrkB in the restricted population of newborn neurons show behavioral deficits, namely increased anxiety-like behavior. These data suggest that the integration and establishment of proper connections by newly generated neurons into the pre-existing network are relevant features for regulating the emotional state of the animal.

Modeling surface-atmosphere exchange of trace gases and energy within and above the Amazon rain forest

Die vorliegende Dissertation untersucht die biogeochemischen Vorgänge in der Vegetationsschicht (Bestand) und die Rückkopplungen zwischen physiologischen und physikalischen Umweltprozessen, die das Klima und die Chemie der unteren Atmosphäre beeinflussen. Ein besondere Schwerpunkt ist die Verwendung theoretischer Ansätze zur Quantifizierung des vertikalen Austauschs von Energie und Spurengasen (Vertikalfluss) unter besonderer Berücksichtigung der Wechselwirkungen der beteiligten Prozesse. Es wird ein differenziertes Mehrschicht-Modell der Vegetation hergeleitet, implementiert, für den amazonischen Regenwald parametrisiert und auf einen Standort in Rondonia (Südwest Amazonien) angewendet, welches die gekoppelten Gleichungen zur Energiebilanz der Oberfläche und CO2-Assimilation auf der Blattskala mit einer Lagrange-Beschreibung des Vertikaltransports auf der Bestandesskala kombiniert. Die hergeleiteten Parametrisierungen beinhalten die vertikale Dichteverteilung der Blattfläche, ein normalisiertes Profil der horizontalen Windgeschwindigkeit, die Lichtakklimatisierung der Photosynthesekapazität und den Austausch von CO2 und Wärme an der Bodenoberfläche. Desweiteren werden die Berechnungen zur Photosynthese, stomatären Leitfähigkeit und der Strahlungsabschwächung im Bestand mithilfe von Feldmessungen evaluiert. Das Teilmodell zum Vertikaltransport wird im Detail unter Verwendung von 222-Radon-Messungen evaluiert. Die ``Vorwärtslösung'' und der ``inverse Ansatz'' des Lagrangeschen Dispersionsmodells werden durch den Vergleich von beobachteten und vorhergesagten Konzentrationsprofilen bzw. Bodenflüssen bewertet. Ein neuer Ansatz wird hergeleitet, um die Unsicherheiten des inversen Ansatzes aus denjenigen des Eingabekonzentrationsprofils zu quantifizieren. Für nächtliche Bedingungen wird eine modifizierte Parametrisierung der Turbulenz vorgeschlagen, welche die freie Konvektion während der Nacht im unteren Bestand berücksichtigt und im Vergleich zu früheren Abschätzungen zu deutlich kürzeren Aufenthaltszeiten im Bestand führt. Die vorhergesagte Stratifizierung des Bestandes am Tage und in der Nacht steht im Einklang mit Beobachtungen in dichter Vegetation. Die Tagesgänge der vorhergesagten Flüsse und skalaren Profile von Temperatur, H2O, CO2, Isopren und O3 während der späten Regen- und Trockenzeit am Rondonia-Standort stimmen gut mit Beobachtungen überein. Die Ergebnisse weisen auf saisonale physiologische Änderungen hin, die sich durch höhere stomatäre Leitfähigkeiten bzw. niedrigere Photosyntheseraten während der Regen- und Trockenzeit manifestieren. Die beobachteten Depositionsgeschwindigkeiten für Ozon während der Regenzeit überschreiten diejenigen der Trockenzeit um 150-250%. Dies kann nicht durch realistische physiologische Änderungen erklärt werden, jedoch durch einen zusätzlichen cuticulären Aufnahmemechanismus, möglicherweise an feuchten Oberflächen. Der Vergleich von beobachteten und vorhergesagten Isoprenkonzentrationen im Bestand weist auf eine reduzierte Isoprenemissionskapazität schattenadaptierter Blätter und zusätzlich auf eine Isoprenaufnahme des Bodens hin, wodurch sich die globale Schätzung für den tropischen Regenwald um 30% reduzieren würde. In einer detaillierten Sensitivitätsstudie wird die VOC Emission von amazonischen Baumarten unter Verwendung eines neuronalen Ansatzes in Beziehung zu physiologischen und abiotischen Faktoren gesetzt. Die Güte einzelner Parameterkombinationen bezüglich der Vorhersage der VOC Emission wird mit den Vorhersagen eines Modells verglichen, das quasi als Standardemissionsalgorithmus für Isopren dient und Licht sowie Temperatur als Eingabeparameter verwendet. Der Standardalgorithmus und das neuronale Netz unter Verwendung von Licht und Temperatur als Eingabeparameter schneiden sehr gut bei einzelnen Datensätzen ab, scheitern jedoch bei der Vorhersage beobachteter VOC Emissionen, wenn Datensätze von verschiedenen Perioden (Regen/Trockenzeit), Blattentwicklungsstadien, oder gar unterschiedlichen Spezies zusammengeführt werden. Wenn dem Netzwerk Informationen über die Temperatur-Historie hinzugefügt werden, reduziert sich die nicht erklärte Varianz teilweise. Eine noch bessere Leistung wird jedoch mit physiologischen Parameterkombinationen erzielt. Dies verdeutlicht die starke Kopplung zwischen VOC Emission und Blattphysiologie.

Periodicities in the Hodgkin-Huxley model and versions of this model with stochastic input

A field of computational neuroscience develops mathematical models to describe neuronal systems. The aim is to better understand the nervous system. Historically, the integrate-and-fire model, developed by Lapique in 1907, was the first model describing a neuron. In 1952 Hodgkin and Huxley [8] described the so called Hodgkin-Huxley model in the article “A Quantitative Description of Membrane Current and Its Application to Conduction and Excitation in Nerve”. The Hodgkin-Huxley model is one of the most successful and widely-used biological neuron models. Based on experimental data from the squid giant axon, Hodgkin and Huxley developed their mathematical model as a four-dimensional system of first-order ordinary differential equations. One of these equations characterizes the membrane potential as a process in time, whereas the other three equations depict the opening and closing state of sodium and potassium ion channels. The membrane potential is proportional to the sum of ionic current flowing across the membrane and an externally applied current. For various types of external input the membrane potential behaves differently. This thesis considers the following three types of input: (i) Rinzel and Miller [15] calculated an interval of amplitudes for a constant applied current, where the membrane potential is repetitively spiking; (ii) Aihara, Matsumoto and Ikegaya [1] said that dependent on the amplitude and the frequency of a periodic applied current the membrane potential responds periodically; (iii) Izhikevich [12] stated that brief pulses of positive and negative current with different amplitudes and frequencies can lead to a periodic response of the membrane potential. In chapter 1 the Hodgkin-Huxley model is introduced according to Izhikevich [12]. Besides the definition of the model, several biological and physiological notes are made, and further concepts are described by examples. Moreover, the numerical methods to solve the equations of the Hodgkin-Huxley model are presented which were used for the computer simulations in chapter 2 and chapter 3. In chapter 2 the statements for the three different inputs (i), (ii) and (iii) will be verified, and periodic behavior for the inputs (ii) and (iii) will be investigated. In chapter 3 the inputs are embedded in an Ornstein-Uhlenbeck process to see the influence of noise on the results of chapter 2.

A physics-based correction model for homogenizing sub-daily temperature series

A new physics-based technique for correcting inhomogeneities present in sub-daily temperature records is proposed. The approach accounts for changes in the sensor-shield characteristics that affect the energy balance dependent on ambient weather conditions (radiation, wind). An empirical model is formulated that reflects the main atmospheric processes and can be used in the correction step of a homogenization procedure. The model accounts for short- and long-wave radiation fluxes (including a snow cover component for albedo calculation) of a measurement system, such as a radiation shield. One part of the flux is further modulated by ventilation. The model requires only cloud cover and wind speed for each day, but detailed site-specific information is necessary. The final model has three free parameters, one of which is a constant offset. The three parameters can be determined, e.g., using the mean offsets for three observation times. The model is developed using the example of the change from the Wild screen to the Stevenson screen in the temperature record of Basel, Switzerland, in 1966. It is evaluated based on parallel measurements of both systems during a sub-period at this location, which were discovered during the writing of this paper. The model can be used in the correction step of homogenization to distribute a known mean step-size to every single measurement, thus providing a reasonable alternative correction procedure for high-resolution historical climate series. It also constitutes an error model, which may be applied, e.g., in data assimilation approaches.

MODELING DIFFERENTIATED TREATMENT EFFECTS FOR MULTIPLE OUTCOMES DATA

Multiple outcomes data are commonly used to characterize treatment effects in medical research, for instance, multiple symptoms to characterize potential remission of a psychiatric disorder. Often either a global, i.e. symptom-invariant, treatment effect is evaluated. Such a treatment effect may over generalize the effect across the outcomes. On the other hand individual treatment effects, varying across all outcomes, are complicated to interpret, and their estimation may lose precision relative to a global summary. An effective compromise to summarize the treatment effect may be through patterns of the treatment effects, i.e. "differentiated effects." In this paper we propose a two-category model to differentiate treatment effects into two groups. A model fitting algorithm and simulation study are presented, and several methods are developed to analyze heterogeneity presenting in the treatment effects. The method is illustrated using an analysis of schizophrenia symptom data.

Golden-winged Warbler habitat model validation for northern Wisconsin and central Minnesota

Between 1966 and 2003, the Golden-winged Warbler (Vermivora chrysoptera) experienced declines of 3.4% per year in large parts of the breeding range and has been identified by Partners in Flight as one of 28 land birds requiring expedient action to prevent its continued decline. It is currently being considered for listing under the Endangered Species Act. A major step in advancing our understanding of the status and habitat preferences of Golden-winged Warbler populations in the Upper Midwest was initiated by the publication of new predictive spatially explicit Golden-winged Warbler habitat models for the northern Midwest. Here, I use original data on observed Golden-winged Warbler abundances in Wisconsin and Minnesota to compare two population models: the hierarchical spatial count (HSC) model with the Habitat Suitability Index (HSI) model. I assessed how well the field data compared to the model predictions and found that within Wisconsin, the HSC model performed slightly better than the HSI model whereas both models performed relatively equally in Minnesota. For the HSC model, I found a 10% error of commission in Wisconsin and a 24.2% error of commission for Minnesota. Similarly, the HSI model has a 23% error of commission in Minnesota; in Wisconsin due to limited areas where the HSI model predicted absences, there was incomplete data and I was unable to determine the error of commission for the HSI model. These are sites where the model predicted presences and the Golden-winged Warbler did not occur. To compare predicted abundance from the two models, a 3x3 contingency table was used. I found that when overlapped, the models do not complement one another in identifying Golden-winged Warbler presences. To calculate discrepancy between the models, the error of commission shows that the HSI model has only a 6.8% chance of correctly classifying absences in the HSC model. The HSC model has only 3.3% chance of correctly classifying absences in the HSI model. These findings highlight the importance of grasses for nesting, shrubs used for cover and foraging, and trees for song perches and foraging as key habitat characteristics for breeding territory occupancy by singing males.

Filtration and oxidation characteristics of a diesel oxidation catalyst and a catalyzed particulate filter : development of a 1-D 2-layer model

The emissions, filtration and oxidation characteristics of a diesel oxidation catalyst (DOC) and a catalyzed particulate filter (CPF) in a Johnson Matthey catalyzed continuously regenerating trap (CCRT ®) were studied by using computational models. Experimental data needed to calibrate the models were obtained by characterization experiments with raw exhaust sampling from a Cummins ISM 2002 engine with variable geometry turbocharging (VGT) and programmed exhaust gas recirculation (EGR). The experiments were performed at 20, 40, 60 and 75% of full load (1120 Nm) at rated speed (2100 rpm), with and without the DOC upstream of the CPF. This was done to study the effect of temperature and CPF-inlet NO2 concentrations on particulate matter oxidation in the CCRT ®. A previously developed computational model was used to determine the kinetic parameters describing the oxidation characteristics of HCs, CO and NO in the DOC and the pressure drop across it. The model was calibrated at five temperatures in the range of 280 – 465° C, and exhaust volumetric flow rates of 0.447 – 0.843 act-m3/sec. The downstream HCs, CO and NO concentrations were predicted by the DOC model to within ±3 ppm. The HCs and CO oxidation kinetics in the temperature range of 280 - 465°C and an exhaust volumetric flow rate of 0.447 - 0.843 act-m3/sec can be represented by one ’apparent’ activation energy and pre-exponential factor. The NO oxidation kinetics in the same temperature and exhaust flow rate range can be represented by ’apparent’ activation energies and pre-exponential factors in two regimes. The DOC pressure drop was always predicted within 0.5 kPa by the model. The MTU 1-D 2-layer CPF model was enhanced in several ways to better model the performance of the CCRT ®. A model to simulate the oxidation of particulate inside the filter wall was developed. A particulate cake layer filtration model which describes particle filtration in terms of more fundamental parameters was developed and coupled to the wall oxidation model. To better model the particulate oxidation kinetics, a model to take into account the NO2 produced in the washcoat of the CPF was developed. The overall 1-D 2-layer model can be used to predict the pressure drop of the exhaust gas across the filter, the evolution of particulate mass inside the filter, the particulate mass oxidized, the filtration efficiency and the particle number distribution downstream of the CPF. The model was used to better understand the internal performance of the CCRT®, by determining the components of the total pressure drop across the filter, by classifying the total particulate matter in layer I, layer II, the filter wall, and by the means of oxidation i.e. by O2, NO2 entering the filter and by NO2 being produced in the filter. The CPF model was calibrated at four temperatures in the range of 280 – 465 °C, and exhaust volumetric flow rates of 0.447 – 0.843 act-m3/sec, in CPF-only and CCRT ® (DOC+CPF) configurations. The clean filter wall permeability was determined to be 2.00E-13 m2, which is in agreement with values in the literature for cordierite filters. The particulate packing density in the filter wall had values between 2.92 kg/m3 - 3.95 kg/m3 for all the loads. The mean pore size of the catalyst loaded filter wall was found to be 11.0 µm. The particulate cake packing densities and permeabilities, ranged from 131 kg/m3 - 134 kg/m3, and 0.42E-14 m2 and 2.00E-14 m2 respectively, and are in agreement with the Peclet number correlations in the literature. Particulate cake layer porosities determined from the particulate cake layer filtration model ranged between 0.841 and 0.814 and decreased with load, which is about 0.1 lower than experimental and more complex discrete particle simulations in the literature. The thickness of layer I was kept constant at 20 µm. The model kinetics in the CPF-only and CCRT ® configurations, showed that no ’catalyst effect’ with O2 was present. The kinetic parameters for the NO2-assisted oxidation of particulate in the CPF were determined from the simulation of transient temperature programmed oxidation data in the literature. It was determined that the thermal and NO2 kinetic parameters do not change with temperature, exhaust flow rate or NO2 concentrations. However, different kinetic parameters are used for particulate oxidation in the wall and on the wall. Model results showed that oxidation of particulate in the pores of the filter wall can cause disproportionate decreases in the filter pressure drop with respect to particulate mass. The wall oxidation model along with the particulate cake filtration model were developed to model the sudden and rapid decreases in pressure drop across the CPF. The particulate cake and wall filtration models result in higher particulate filtration efficiencies than with just the wall filtration model, with overall filtration efficiencies of 98-99% being predicted by the model. The pre-exponential factors for oxidation by NO2 did not change with temperature or NO2 concentrations because of the NO2 wall production model. In both CPF-only and CCRT ® configurations, the model showed NO2 and layer I to be the dominant means and dominant physical location of particulate oxidation respectively. However, at temperatures of 280 °C, NO2 is not a significant oxidizer of particulate matter, which is in agreement with studies in the literature. The model showed that 8.6 and 81.6% of the CPF-inlet particulate matter was oxidized after 5 hours at 20 and 75% load in CCRT® configuration. In CPF-only configuration at the same loads, the model showed that after 5 hours, 4.4 and 64.8% of the inlet particulate matter was oxidized. The increase in NO2 concentrations across the DOC contributes significantly to the oxidation of particulate in the CPF and is supplemented by the oxidation of NO to NO2 by the catalyst in the CPF, which increases the particulate oxidation rates. From the model, it was determined that the catalyst in the CPF modeslty increases the particulate oxidation rates in the range of 4.5 – 8.3% in the CCRT® configuration. Hence, the catalyst loading in the CPF of the CCRT® could possibly be reduced without significantly decreasing particulate oxidation rates leading to catalyst cost savings and better engine performance due to lower exhaust backpressures.

Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

A new methodological protocol for the use of dendrogeomorphological data in flood risk analysis

Dendrogeomorphology uses information sources recorded in the roots, trunks and branches of trees and bushes located in the fluvial system to complement (or sometimes even replace) systematic and palaeohydrological records of past floods. The application of dendrogeomorphic data sources and methods to palaeoflood analysis over nearly 40 years has allowed improvements to be made in frequency and magnitude estimations of past floods. Nevertheless, research carried out so far has shown that the dendrogeomorphic indicators traditionally used (mainly scar evidence), and their use to infer frequency and magnitude, have been restricted to a small, limited set of applications. New possibilities with enormous potential remain unexplored. New insights in future research of palaeoflood frequency and magnitude using dendrogeomorphic data sources should: (1) test the application of isotopic indicators (16O/18O ratio) to discover the meteorological origin of past floods; (2) use different dendrogeomorphic indicators to estimate peak flows with 2D (and 3D) hydraulic models and study how they relate to other palaeostage indicators; (3) investigate improved calibration of 2D hydraulic model parameters (roughness); and (4) apply statistics-based cost–benefit analysis to select optimal mitigation measures. This paper presents an overview of these innovative methodologies, with a focus on their capabilities and limitations in the reconstruction of recent floods and palaeofloods.

Involvement of heparin-like glycosaminoglycans and expression of a novel heparan sulfate binding protein (p24) during human placentation and in a model for human implantation

Previous studies in our laboratory have indicated that heparan sulfate proteoglycans (HSPGs) play an important role in murine embryo implantation. To investigate the potential function of HSPGs in human implantation, two human cell lines (RL95 and JAR) were selected to model uterine epithelium and embryonal trophectoderm, respectively. A heterologous cell-cell adhesion assay showed that initial binding between JAR and RL95 cells is mediated by cell surface glycosaminoglycans (GAG) with heparin-like properties, i.e., heparan sulfate and dermatan sulfate. Furthermore, a single class of highly specific, protease-sensitive heparin/heparan sulfate binding sites exist on the surface of RL95 cells. Three heparin binding, tryptic peptide fragments were isolated from RL95 cell surfaces and their amino termini partially sequenced. Reverse transcription-polymerase chain reaction (RT-PCR) generated 1 to 4 PCR products per tryptic peptide. Northern blot analysis of RNA from RL95 cells using one of these RT-PCR products identified a 1.2 Kb mRNA species (p24). The amino acid sequence predicted from the cDNA sequence contains a putative heparin-binding domain. A synthetic peptide representing this putative heparin binding domain was used to generate a rabbit polyclonal antibody (anti-p24). Indirect immunofluorescence studies on RL95 and JAR cells as well as binding studies of anti-p24 to intact RL95 cells demonstrate that p24 is distributed on the cell surface. Western blots of RL95 membrane preparations identify a 24 kDa protein (p24) highly enriched in the 100,000 g pellet plasma membrane-enriched fraction. p24 eluted from membranes with 0.8 M NaCl, but not 0.6 M NaCl, suggesting that it is a peripheral membrane component. Solubilized p24 binds heparin by heparin affinity chromatography and $\sp{125}$I-heparin binding assays. Furthermore, indirect immunofluorescence studies indicate that cytotrophoblast of floating and attached villi of the human fetal-maternal interface are recognized by anti-p24. The study also indicates that the HSPG, perlecan, accumulates where chorionic villi are attached to uterine stroma and where p24-expressing cytotrophoblast penetrate the stroma. Collectively, these data indicate that p24 is a cell surface membrane-associated heparin/heparan sulfate binding protein found in cytotrophoblast, but not many other cell types of the fetal-maternal interface. Furthermore, p24 colocalizes with HSPGs in regions of cytotrophoblast invasion. These observations are consistent with a role for HSPGs and HSPG binding proteins in human trophoblast-uterine cell interactions. ^