Effect of different management intensities on natural and human-induced carbon fluxes in a golf course in northern Italy

Turfgrasses are ubiquitous in urban landscape and their role on carbon (C) cycle is increasing important also due to the considerable footprint related to their management practices. It is crucial to understand the mechanisms driving the C assimilation potential of these terrestrial ecosystems Several approaches have been proposed to assess C dynamics: micro-meteorological methods, small-chamber enclosure system (SC), chrono-sequence approach and various models. Natural and human-induced variables influence turfgrasses C fluxes. Species composition, environmental conditions, site characteristics, former land use and agronomic management are the most important factors considered in literature driving C sequestration potential. At the same time different approaches seem to influence C budget estimates. In order to study the effect of different management intensities on turfgrass, we estimated net ecosystem exchange (NEE) through a SC approach in a hole of a golf course in the province of Verona (Italy) for one year. The SC approach presented several advantages but also limits related to the measurement frequency, timing and duration overtime, and to the methodological errors connected to the measuring system. Daily CO2 fluxes changed according to the intensity of maintenance, likely due to different inputs and disturbances affecting biogeochemical cycles, combined also to the different leaf area index (LAI). The annual cumulative NEE decreased with the increase of the intensity of management. NEE was related to the seasonality of turfgrass, following temperatures and physiological activity. Generally on the growing season CO2 fluxes towards atmosphere exceeded C sequestered. The cumulative NEE showed a system near to a steady state for C dynamics. In the final part greenhouse gases (GHGs) emissions due to fossil fuel consumption for turfgrass upkeep were estimated, pinpointing that turfgrass may result a considerable C source. The C potential of trees and shrubs needs to be considered to obtain a complete budget.

On the Luminous and Dark Matter Distribution in Early-Type Galaxies

The way mass is distributed in galaxies plays a major role in shaping their evolution across cosmic time. The galaxy's total mass is usually determined by tracing the motion of stars in its potential, which can be probed observationally by measuring stellar spectra at different distances from the galactic centre, whose kinematics is used to constrain dynamical models. A class of such models, commonly used to accurately determine the distribution of luminous and dark matter in galaxies, is that of equilibrium models. In this Thesis, a novel approach to the design of equilibrium dynamical models, in which the distribution function is an analytic function of the action integrals, is presented. Axisymmetric and rotating models are used to explain observations of a sample of nearby early-type galaxies in the Calar Alto Legacy Integral Field Area survey. Photometric and spectroscopic data for round and flattened galaxies are well fitted by the models, which are then used to get the galaxies' total mass distribution and orbital anisotropy. The time evolution of massive early-type galaxies is also investigated with numerical models. Their structural properties (mass, size, velocity dispersion) are observed to evolve, on average, with redshift. In particular, they appear to be significantly more compact at higher redshift, at fixed stellar mass, so it is interesting to investigate what drives such evolution. This Thesis focuses on the role played by dark-matter haloes: their mass-size and mass-velocity dispersion correlations evolve similarly to the analogous correlations of ellipticals; at fixed halo mass, the haloes are more compact at higher redshift, similarly to massive galaxies; a simple model, in which all the galaxy's size and velocity-dispersion evolution is due to the cosmological evolution of the underlying halo population, reproduces the observed size and velocity-dispersion of massive compact early-type galaxies up to redshift of about 2.

Volatile organic compounds at the air-sea interface : gas exchange rates, oceanic emissions and the effect of ocean acidification

Oceans are key sources and sinks in the global budgets of significant atmospheric trace gases, termed Volatile Organic Compounds (VOCs). Despite their low concentrations, these species have an important role in the atmosphere, influencing ozone photochemistry and aerosol physics. Surprisingly, little work has been done on assessing their emissions or transport mechanisms and rates between ocean and atmosphere, all of which are important when modelling the atmosphere accurately.rnA new Needle Trap Device (NTD) - GC-MS method was developed for the effective sampling and analysis of VOCs in seawater. Good repeatability (RSDs <16 %), linearity (R2 = 0.96 - 0.99) and limits of detection in the range of pM were obtained for DMS, isoprene, benzene, toluene, p-xylene, (+)-α-pinene and (-)-α-pinene. Laboratory evaluation and subsequent field application indicated that the proposed method can be used successfully in place of the more usually applied extraction techniques (P&T, SPME) to extend the suite of species typically measured in the ocean and improve detection limits. rnDuring a mesocosm CO2 enrichment study, DMS, isoprene and α-pinene were identified and quantified in seawater samples, using the above mentioned method. Based on correlations with available biological datasets, the effects of ocean acidification as well as possible ocean biological sources were investigated for all examined compounds. Future ocean's acidity was shown to decrease oceanic DMS production, possibly impact isoprene emissions but not affect the production of α-pinene. rnIn a separate activity, ocean - atmosphere interactions were simulated in a large scale wind-wave canal facility, in order to investigate the gas exchange process and its controlling mechanisms. Air-water exchange rates of 14 chemical species (of which 11 VOCs) spanning a wide range of solubility (dimensionless solubility, α = 0:4 to 5470) and diffusivity (Schmidt number in water, Scw = 594 to 1194) were obtained under various turbulent (wind speed at ten meters height, u10 = 0:8 to 15ms-1) and surfactant modulated (two different sized Triton X-100 layers) surface conditions. Reliable and reproducible total gas transfer velocities were obtained and the derived values and trends were comparable to previous investigations. Through this study, a much better and more comprehensive understanding of the gas exchange process was accomplished. The role of friction velocity, uw* and mean square slope, σs2 in defining phenomena such as waves and wave breaking, near surface turbulence, bubbles and surface films was recognized as very significant. uw* was determined as the ideal turbulent parameter while σs2 described best the related surface conditions. A combination of both uw* and σs2 variables, was found to reproduce faithfully the air-water gas exchange process. rnA Total Transfer Velocity (TTV) model provided by a compilation of 14 tracers and a combination of both uw* and σs2 parameters, is proposed for the first time. Through the proposed TTV parameterization, a new physical perspective is presented which provides an accurate TTV for any tracer within the examined solubility range. rnThe development of such a comprehensive air-sea gas exchange parameterization represents a highly useful tool for regional and global models, providing accurate total transfer velocity estimations for any tracer and any sea-surface status, simplifying the calculation process and eliminating inevitable calculation uncertainty connected with the selection or combination of different parameterizations.rnrn

Thermal structure and dynamical modeling of a Mediterranean tropical-like cyclone

In the present work, a detailed analysis of a Mediterranean TLC occurred in January 2014 has been conducted. The author is not aware of other studies regarding this particular event at the publication of this thesis. In order to outline the cyclone evolution, observational data, including weather-stations data, satellite data, radar data and photographic evidence, were collected at first. After having identified the cyclone path and its general features, the GLOBO, BOLAM and MOLOCH NWP models, developed at ISAC-CNR (Bologna), were used to simulate the phenomenon. Particular attention was paid on the Mediterranean phase as well as on the Atlantic phase, since the cyclone showed a well defined precursor up to 3 days before the minimum formation in the Alboran Sea. The Mediterranean phase has been studied using different combinations of GLOBO, BOLAM and MOLOCH models, so as to evaluate the best model chain to simulate this kind of phenomena. The BOLAM and MOLOCH models showed the best performance, by adjusting the path erroneously deviated in the National Centre for Environmental Prediction (NCEP) and ECMWF operational models. The analysis of the cyclone thermal phase shown the presence of a deep-warm core structure in many cases, thus confirming the tropical-like nature of the system. Furthermore, the results showed high sensitivity to initial conditions in the whole lifetime of the cyclone, while the Sea Surface Temperature (SST) modification leads only to small changes in the Adriatic phase. The Atlantic phase has been studied using GLOBO and BOLAM model and with the aid of the same methodology already developed. After tracing the precursor, in the form of a low-pressure system, from the American East Coast to Spain, the thermal phase analysis was conducted. The parameters obtained showed evidence of a deep-cold core asymmetric structure during the whole Atlantic phase, while the first contact with the Mediterranean Sea caused a sudden transition to a shallow-warm core structure. The examination of Potential Vorticity (PV) 3-dimensional structure revealed the presence of a PV streamer that individually formed over Greenland and eventually interacted with the low-pressure system over the Spanish coast, favouring the first phase of the cyclone baroclinic intensification. Finally, the development of an automated system that tracks and studies the thermal phase of Mediterranean cyclones has been encouraged. This could lead to the forecast of potential tropical transition, against with a minimum computational investment.

Design and implementation of the ESEO spacecraft simulator

The thesis work is developed under the European Student Earth Orbiter (ESEO) project supported by the European Space Agency (ESA) in order to help prepare a well-qualified space-engineering workforce for Europe's future. In the following chapters we are going to analyse how to simulate some ESEO subsystem. First of all, the Thermal Subsystem that evaluates the temperature evolution of on-board instruments. For this purpose, simulating also the orbital and attitude dynamics of the spacecraft, it is necessary in order to evaluate external environmental fluxes. The Power Subsystem will be the following step and it models the ability of a spacecraft to produce and store electrical energy. Finally, we will integrate in our software a block capable of simulating the communication link between the satellite and the Ground Station (GS). This last step is designed and validated during the thesis preparation.

A comparison between 2D and 3D cephalometry on CBCT scans of human skulls

The purpose of this study was to evaluate whether measurements on conventional cephalometric radiographs are comparable with 3D measurements on 3D models of human skulls, derived from cone beam CT (CBCT) data. A CBCT scan and a conventional cephalometric radiograph were made of 40 dry skulls. Standard cephalometric software was used to identify landmarks on both the 2D images and the 3D models. The same operator identified 17 landmarks on the cephalometric radiographs and on the 3D models. All images and 3D models were traced five times with a time-interval of 1 week and the mean value of repeated measurements was used for further statistical analysis. Distances and angles were calculated. Intra-observer reliability was good for all measurements. The reproducibility of the measurements on the conventional cephalometric radiographs was higher compared with the reproducibility of measurements on the 3D models. For a few measurements a clinically relevant difference between measurements on conventional cephalometric radiographs and 3D models was found. Measurements on conventional cephalometric radiographs can differ significantly from measurements on 3D models of the same skull. The authors recommend that 3D tracings for longitudinal research are not used in cases were there are only 2D records from the past.

Standard intracranial in vivo animal models of delayed cerebral vasospasm

Animal models provide a basis for clarifying the complex pathogenesis of delayed cerebral vasospasm (DCVS) and for screening of potential therapeutic approaches. Arbitrary use of experimental parameters in current models can lead to results of uncertain relevance. The aim of this work was to identify and analyze the most consistent and feasible models and their parameters for each animal.

The genetic basis of craniofacial and dental abnormalities

The embryonic head development, including the formation of dental structures, is a complex and delicate process guided by specific genetic programs. Genetic changes and environmental factors can disturb the execution of these programs and result in abnormalities in orofacial and dental structures. Orofacial clefts and hypodontia/ oligodontia are examples of such abnormalities frequently seen in dental clinics. An insight into the mechanisms and genes involved in the formation of orofacial and dental structures has been gradually gained by genetic analysis of families and by the use of experimental vertebrate models such as the mouse and chick models. The development of novel clinical therapies for orofacial and dental pathological conditions depends very much on a detailed knowledge of the molecular and cellular processes that are involved in head formation.

Functional Imaging of Pheochromocytoma with Ga-DOTATOC and C-HED in a Genetically Defined Rat Model of Multiple Endocrine Neoplasia

Rats affected by the MENX multitumor syndrome develop pheochromocytoma (100%). Pheochromocytomas are uncommon tumors and animal models are scarce, hence the interest in MENX rats to identify and preclinically evaluate novel targeted therapies. A prerequisite for such studies is a sensitive and noninvasive detection of MENXassociated pheochromocytoma. We performed positron emission tomography (PET) to determine whether rat pheochromocytomas are detected by tracers used in clinical practice, such as 68Ga-DOTATOC (somatostatin analogue) or (11)C-Hydroxyephedrine (HED), a norepinephrine analogue. We analyzed four affected and three unaffected rats. The PET scan findings were correlated to histopathology and immunophenotype of the tumors, their proliferative index, and the expression of genes coding for somatostatin receptors or the norepinephrine transporter. We observed that mean 68Ga-DOTATOC standard uptake value (SUV) in adrenals of affected animals was 23.3 ± 3.9, significantly higher than in control rats (15.4 ± 7.9; P = .03). The increase in mean tumor-to-liver ratio of (11)C-HED in the MENX-affected animals (1.6 ± 0.5) compared to controls (0.7 ± 0.1) was even more significant (P = .0016). In a unique animal model, functional imaging depicting two pathways important in pheochromocytoma biology discriminated affected animals from controls, thus providing the basis for future preclinical work with MENX rats.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

Computational Design and Experimental Discovery of an Anti-estrogenic Peptide Derived from Alpha-Fetoprotein

Breast cancer is the most common cancer among women, and tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment. Many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Consequently, there is an ongoing need for breast cancer drugs that have different molecular targets. Previous work has shown that 8-mer and cyclic 9-mer peptides inhibit breast cancer in mouse and rat models, interacting with an unsolved receptor, while peptides smaller than eight amino acids did not. We show that the use of replica exchange molecular dynamics predicts the structure and dynamics of active peptides, leading to the discovery of smaller peptides with full biological activity. Simulations identified smaller peptide analogues with the same conserved reverse turn demonstrated in the larger peptides. These analogues were synthesized and shown to inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition.

Estimating loss to follow-up in HIV-infected patients on antiretroviral therapy: the effect of the competing risk of death in Zambia and Switzerland

Background Loss to follow-up (LTFU) is common in antiretroviral therapy (ART) programmes. Mortality is a competing risk (CR) for LTFU; however, it is often overlooked in cohort analyses. We examined how the CR of death affected LTFU estimates in Zambia and Switzerland. Methods and Findings HIV-infected patients aged ≥18 years who started ART 2004–2008 in observational cohorts in Zambia and Switzerland were included. We compared standard Kaplan-Meier curves with CR cumulative incidence. We calculated hazard ratios for LTFU across CD4 cell count strata using cause-specific Cox models, or Fine and Gray subdistribution models, adjusting for age, gender, body mass index and clinical stage. 89,339 patients from Zambia and 1,860 patients from Switzerland were included. 12,237 patients (13.7%) in Zambia and 129 patients (6.9%) in Switzerland were LTFU and 8,498 (9.5%) and 29 patients (1.6%), respectively, died. In Zambia, the probability of LTFU was overestimated in Kaplan-Meier curves: estimates at 3.5 years were 29.3% for patients starting ART with CD4 cells <100 cells/µl and 15.4% among patients starting with ≥350 cells/µL. The estimates from CR cumulative incidence were 22.9% and 13.6%, respectively. Little difference was found between naïve and CR analyses in Switzerland since only few patients died. The results from Cox and Fine and Gray models were similar: in Zambia the risk of loss to follow-up and death increased with decreasing CD4 counts at the start of ART, whereas in Switzerland there was a trend in the opposite direction, with patients with higher CD4 cell counts more likely to be lost to follow-up. Conclusions In ART programmes in low-income settings the competing risk of death can substantially bias standard analyses of LTFU. The CD4 cell count and other prognostic factors may be differentially associated with LTFU in low-income and high-income settings.

Antinociceptive efficacy and plasma concentrations of transdermal buprenorphine in dogs

To assess the antinociceptive efficacy of transdermal (TD) buprenorphine (B) in dogs, a prospective, positive-controlled experimental study was performed in 10 healthy Beagles. In an open label crossover design, the dogs initially received intravenous B (IVB, 0.02 mg kg(-1)) as a positive control, followed by TDB (52.5 mug h(-1)) 4 months later. Blood was collected at regular intervals for determination of the plasma concentrations of B ([B]) and its metabolite norbuprenorphine. The antinociceptive efficacy was assessed using thermal and mechanical models of nociception. The peak concentration [B] was 1.54 ng mL(-1) (+/-1.98) 60 h after TDB application, although three dogs had no measurable [B] after TDB. Maximum thermal threshold (TT) was 52.6 degrees C (+/-0.48) at 1h after IVB administration and 51.63 degrees C (+/-1.01) 72 h after TDB application. The significant increase in TT indicated that effective antinociception was achieved beyond 36 h after the application of TDB, lasting until patch removal. There was hysteresis between [B] and the antinociceptive effect.

Individual and population level effects of partner notification for Chlamydia trachomatis

Partner notification (PN or contact tracing) is an important aspect of treating bacterial sexually transmitted infections (STIs), such as Chlamydia trachomatis. It facilitates the identification of new infected cases that can be treated through individual case management. PN also acts indirectly by limiting onward transmission in the general population. However, the impact of PN, both at the level of individuals and the population, remains unclear. Since it is difficult to study the effects of PN empirically, mathematical and computational models are useful tools for investigating its potential as a public health intervention. To this end, we developed an individual-based modeling framework called Rstisim. It allows the implementation of different models of STI transmission with various levels of complexity and the reconstruction of the complete dynamic sexual partnership network over any time period. A key feature of this framework is that we can trace an individual's partnership history in detail and investigate the outcome of different PN strategies for C. trachomatis. For individual case management, the results suggest that notifying three or more partners from the preceding 18 months yields substantial numbers of new cases. In contrast, the successful treatment of current partners is most important for preventing re-infection of index cases and reducing further transmission of C. trachomatis at the population level. The findings of this study demonstrate the difference between individual and population level outcomes of public health interventions for STIs.

Metabolomics reveals the metabolic map of procainamide in humans and mice

Procainamide, a type I antiarrhythmic agent, is used to treat a variety of atrial and ventricular dysrhythmias. It was reported that long-term therapy with procainamide may cause lupus erythematosus in 25-30% of patients. Interestingly, procainamide does not induce lupus erythematosus in mouse models. To explore the differences in this side-effect of procainamide between humans and mouse models, metabolomic analysis using ultra-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-QTOFMS) was conducted on urine samples from procainamide-treated humans, CYP2D6-humanized mice, and wild-type mice. Thirteen urinary procainamide metabolites, including nine novel metabolites, derived from P450-dependent, FMO-dependent oxidations and acylation reactions, were identified and structurally elucidated. In vivo metabolism of procainamide in CYP2D6-humanized mice as well as in vitro incubations with microsomes and recombinant P450s suggested that human CYP2D6 plays a major role in procainamide metabolism. Significant differences in N-acylation and N-oxidation of the drug between humans and mice largely account for the interspecies differences in procainamide metabolism. Significant levels of the novel N-oxide metabolites produced by FMO1 and FMO3 in humans might be associated with the development of procainamide-induced systemic lupus erythematosus. Observations based on this metabolomic study offer clues to understanding procainamide-induced lupus in humans and the effect of P450s and FMOs on procainamide N-oxidation.