VALIDATION OF A 'DISPLACEMENT TOMOGRAPHY' INVERSION METHOD FOR MODELING SHEET INTRUSIONS

The study of volcano deformation data can provide information on magma processes and help assess the potential for future eruptions. In employing inverse deformation modeling on these data, we attempt to characterize the geometry, location and volume/pressure change of a deformation source. Techniques currently used to model sheet intrusions (e.g., dikes and sills) often require significant a priori assumptions about source geometry and can require testing a large number of parameters. Moreover, surface deformations are a non-linear function of the source geometry and location. This requires the use of Monte Carlo inversion techniques which leads to long computation times. Recently, ‘displacement tomography’ models have been used to characterize magma reservoirs by inverting source deformation data for volume changes using a grid of point sources in the subsurface. The computations involved in these models are less intensive as no assumptions are made on the source geometry and location, and the relationship between the point sources and the surface deformation is linear. In this project, seeking a less computationally intensive technique for fracture sources, we tested if this displacement tomography method for reservoirs could be used for sheet intrusions. We began by simulating the opening of three synthetic dikes of known geometry and location using an established deformation model for fracture sources. We then sought to reproduce the displacements and volume changes undergone by the fractures using the sources employed in the tomography methodology. Results of this validation indicate the volumetric point sources are not appropriate for locating fracture sources, however they may provide useful qualitative information on volume changes occurring in the surrounding rock, and therefore indirectly indicate the source location.

Geographic Provenancing of Unprocessed Cotton Using Elemental Analysis and Stable Isotope Ratios

Cotton is the most abundant natural fiber in the world. Many countries are involved in the growing, importation, exportation and production of this commodity. Paper documentation claiming geographic origin is the current method employed at U.S. ports for identifying cotton sources and enforcing tariffs. Because customs documentation can be easily falsified, it is necessary to develop a robust method for authenticating or refuting the source of the cotton commodities. This work presents, for the first time, a comprehensive approach to the chemical characterization of unprocessed cotton in order to provide an independent tool to establish geographic origin. Elemental and stable isotope ratio analysis of unprocessed cotton provides a means to increase the ability to distinguish cotton in addition to any physical and morphological examinations that could be, and are currently performed. Elemental analysis has been conducted using LA-ICP-MS, LA-ICP-OES and LIBS in order to offer a direct comparison of the analytical performance of each technique and determine the utility of each technique for this purpose. Multivariate predictive modeling approaches are used to determine the potential of elemental and stable isotopic information to aide in the geographic provenancing of unprocessed cotton of both domestic and foreign origin. These approaches assess the stability of the profiles to temporal and spatial variation to determine the feasibility of this application. This dissertation also evaluates plasma conditions and ablation processes so as to improve the quality of analytical measurements made using atomic emission spectroscopy techniques. These interactions, in LIBS particularly, are assessed to determine any potential simplification of the instrumental design and method development phases. This is accomplished through the analysis of several matrices representing different physical substrates to determine the potential of adopting universal LIBS parameters for 532 nm and 1064 nm LIBS for some important operating parameters. A novel approach to evaluate both ablation processes and plasma conditions using a single measurement was developed and utilized to determine the “useful ablation efficiency” for different materials. The work presented here demonstrates the potential for an a priori prediction of some probable laser parameters important in analytical LIBS measurement.

Determining magmatic processes from analysis of phenocrysts and gabbroic xenoliths contained in Calbuco andesites

Calbuco Volcano, in Southern Chile, has eruptive products of predominantly andesitic hornblende-bearing lava. A purpose of this work is to understand magmatic processes and how Calbuco magma chemistry is related to the explosive volcanic character. Calbuco lava has a mineral assemblage of plagioclase, hornblende, orthopyroxene, clinopyroxene, olivine, and magnetite and entrained gabbroic xenoliths with the same mineral assemblage. The presence of hornblende is evidence for dissolved water in the magma. Detailed petrographic/textural analysis has been done using petrographic microscopy and back-scattered electron imaging (BSE); geochemical analysis by electron microprobe (EPMA). Major findings include 1) that hornblende and hornblende-bearing gabbroic cumulates crystallize from Calbuco magma, 2) that plagioclase grains are compositionally zoned, recording evidence of temperature, chemical, and water content fluctuations in the magma, and 3) that hornblende is unstable under upper magma chamber conditions at Calbuco, and is breaking down into plagioclase, olivine, orthopyroxene, clinopyroxene, and magnetite in the magma.

Advanced Methodologies in Dynamic Traffic Assignment Modeling of Managed Lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.

AD-HOC principles of minimum energy expenditure as corollaries of the constructal law the cases of river basins and human vascular systems

In a recent paper [1] Reis showed that both the principles of extremum of entropy production rate, which are often used in the study of complex systems, are corollaries of the Constructal Law. In fact, both follow from the maximization of overall system conductivities, under appropriate constraints. In this way, the maximum rate of entropy production (MEP) occurs when all the forces in the system are kept constant. On the other hand, the minimum rate of entropy production (mEP) occurs when all the currents that cross the system are kept constant. In this paper it is shown how the so-called principle of "minimum energy expenditure" which is often used as the basis for explaining many morphologic features in biologic systems, and also in inanimate systems, is also a corollary of Bejan's Constructal Law [2]. Following the general proof some cases namely, the scaling laws of human vascular systems and river basins are discussed as illustrations from the side of life, and inanimate systems, respectively.

Water and sediments geochemistry and elemental fluxes on a Large Dam: case study of Ridracoli reservoir.

Since the study of Large Dam Reservoirs is of worldwide interest, in this PhD project we investigated the Ridracoli reservoir, one of the main water supply in Emilia-Romagna (north-eastern Italy). This work aims to characterize waters and sediments to better understand their composition, interactions and any process that occurs, for a better geochemical and environmental knowledge of the area. Physical and chemical analyses on the water column have shown an alternation of stratification and mixing of water in the reservoir’s water body due to seasonal variations in temperature and density. In particular, it was observed the establishment, in late summer, of anoxic conditions at the bottom, which in turn affects the concentration and mobility of some elements of concern (e.g. Fe and Mn) for the water quality. Sediments within the reservoir and from surrounding areas were analysed for organic matter, total inorganic composition and grain size, assessing the inter-element relationship, grain size, geological background and damming influences on their chemistry, through descriptive statistics, Principal Component Analysis and Cluster Analysis. The reservoir’s area was also investigated by pseudo total composition (Aqua Regia digestion), degree of elements extractability, and enrichment factors, then analysed and compared to limits by law and literature. Sediment cores, interstitial waters, and benthic chamber data from the bottom were of great interest due to organic matter degradation, early diagenesis, mineral formation at water-sediment interface and observed flows. Finally, leaching test and extraction procedures, of environmental interest, showed peculiar partitioning, both regarding spatial and in-depth distribution, and the absence of pollution. Collectively, our results are useful for the comprehension of processes that occur in water and sediments of Ridracoli reservoir, providing important knowledges on the site that could be relevant for the management of the resource and the planning of future interventions.

Methods for integrating machine learning and constrained optimization

In the framework of industrial problems, the application of Constrained Optimization is known to have overall very good modeling capability and performance and stands as one of the most powerful, explored, and exploited tool to address prescriptive tasks. The number of applications is huge, ranging from logistics to transportation, packing, production, telecommunication, scheduling, and much more. The main reason behind this success is to be found in the remarkable effort put in the last decades by the OR community to develop realistic models and devise exact or approximate methods to solve the largest variety of constrained or combinatorial optimization problems, together with the spread of computational power and easily accessible OR software and resources. On the other hand, the technological advancements lead to a data wealth never seen before and increasingly push towards methods able to extract useful knowledge from them; among the data-driven methods, Machine Learning techniques appear to be one of the most promising, thanks to its successes in domains like Image Recognition, Natural Language Processes and playing games, but also the amount of research involved. The purpose of the present research is to study how Machine Learning and Constrained Optimization can be used together to achieve systems able to leverage the strengths of both methods: this would open the way to exploiting decades of research on resolution techniques for COPs and constructing models able to adapt and learn from available data. In the first part of this work, we survey the existing techniques and classify them according to the type, method, or scope of the integration; subsequently, we introduce a novel and general algorithm devised to inject knowledge into learning models through constraints, Moving Target. In the last part of the thesis, two applications stemming from real-world projects and done in collaboration with Optit will be presented.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Granulocyte Colony-stimulating Factor (g-csf) Positive Effects On Muscle Fiber Degeneration And Gait Recovery After Nerve Lesion In Mdx Mice.

G-CSF has been shown to decrease inflammatory processes and to act positively on the process of peripheral nerve regeneration during the course of muscular dystrophy. The aims of this study were to investigate the effects of treatment of G-CSF during sciatic nerve regeneration and histological analysis in the soleus muscle in MDX mice. Six-week-old male MDX mice underwent left sciatic nerve crush and were G-CSF treated at 7 days prior to and 21 days after crush. Ten and twenty-one days after surgery, the mice were euthanized, and the sciatic nerves were processed for immunohistochemistry (anti-p75(NTR) and anti-neurofilament) and transmission electron microscopy. The soleus muscles were dissected out and processed for H&E staining and subsequent morphologic analysis. Motor function analyses were performed at 7 days prior to and 21 days after sciatic crush using the CatWalk system and the sciatic nerve index. Both groups treated with G-CSF showed increased p75(NTR) and neurofilament expression after sciatic crush. G-CSF treatment decreased the number of degenerated and regenerated muscle fibers, thereby increasing the number of normal muscle fibers. The reduction in p75(NTR) and neurofilament indicates a decreased regenerative capacity in MDX mice following a lesion to a peripheral nerve. The reduction in motor function in the crushed group compared with the control groups may reflect the cycles of muscle degeneration/regeneration that occur postnatally. Thus, G-CSF treatment increases motor function in MDX mice. Nevertheless, the decrease in baseline motor function in these mice is not reversed completely by G-CSF.

Ecological Literacy And Beyond: Problem-based Learning For Future Professionals.

Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.

Photocatalytic Degradation Of Ofloxacin And Evaluation Of The Residual Antimicrobial Activity.

Ofloxacin is an antimicrobial agent frequently found in significant concentrations in wastewater and surface water. Its continuous introduction into the environment is a potential risk to non-target organisms or to human health. In this study, ofloxacin degradation by UV/TiO2 and UV/TiO2/H2O2, antimicrobial activity (E. coli) of samples subjected to these processes, and by-products formed were evaluated. For UV/TiO2, the degradation efficiency was 89.3% in 60 min of reaction when 128 mg L(-1) TiO2 were used. The addition of 1.68 mmol L(-1) hydrogen peroxide increased degradation to 97.8%. For UV/TiO2, increasing the catalyst concentration from 4 to 128 mg L(-1) led to an increase in degradation efficiency. For both processes, the antimicrobial activity was considerably reduced throughout the reaction time. The structures of two by-products are presented: m/z 291 (9-fluoro-3-methyl-10-(methyleneamino)-7-oxo-2,3-dihydro-7H-[1,4]oxazino[2,3,4-ij]quinoline-6-carboxylic acid) and m/z 157 ((Z)-2-formyl-3-((2-oxoethyl)imino)propanoic acid).

Trends and strategies of ozone application in environmental problems

Efforts presented by the scientific community in recent years towards the development of numerous green chemical processes and wastewater treatment technologies are presented and discussed. In the light of these approaches, environmentally friendly technologies, as well as the key role played by the well-known advanced oxidation processes, are discussed, giving special attention to the ones comprising ozone applications. Fundamentals and applied aspects dealing with ozone technology and its application are also presented.

Myoglobins: the link between discoloration and lipid oxidation in muscle and meat

Aerobic metabolism changes rapidly to glycolysis post-mortem resulting in a pH-decrease during the transformation of muscle in to meat affecting ligand binding and redox potential of the heme iron in myoglobin, the meat pigment. The inorganic chemistry of meat involves (i) redox-cycling between iron(II), iron(III), and iron(IV)/protein radicals; (ii) ligand exchange processes; and (iii) spin-equilibra with a change in coordination number for the heme iron. In addition to the function of myoglobin for oxygen storage, new physiological roles of myoglobin are currently being discovered, which notably find close parallels in the processes in fresh meat and nitrite-cured meat products. Myoglobin may be characterized as a bioreactor for small molecules like O2, NO, CO, CO2, H2O, and HNO with importance in bio-regulation and in protection against oxidative stress in vivo otherwise affecting lipids in membranes. Many of these processes may be recognised as colour changes in fresh meat and cured meat products under different atmospheric conditions, and could also be instructive for teaching purposes.

Acupuncture for the prevention of radiation-induced xerostomia in patients with head and neck cancer

The aim of this study was to evaluate the effectiveness of acupuncture in minimizing the severity of radiation-induced xerostomia in patients with head and neck cancer. A total of 24 consecutive patients receiving > 5000 cGy radiotherapy (RT) involving the major salivary glands bilaterally were assigned to either the preventive acupuncture group (PA, n = 12), treated with acupuncture before and during RT, or the control group (CT, n = 12), treated with RT and not receiving acupuncture. After RT completion, clinical response was assessed in all patients by syalometry, measuring the resting (RSFR) and stimulated (SSFR) salivary flow rates, and by the visual analogue scale (VAS) regarding dry mouth-related symptoms. Statistical analyses were performed with repeated-measures using a mixed-effect modeling procedure and analysis of variance. An alpha level of 0.05 was accepted for statistical significance. Although all patients exhibited some degree of impairment in salivary gland functioning after RT, significant differences were found between the groups. Patients in the PA group showed improved salivary flow rates (RSFR, SSFR; p < 0.001) and decreased xerostomia-related symptoms (VAS, p < 0.05) compared with patients in the CT group. Although PA treatment did not prevent the oral sequelae of RT completely, it significantly minimized the severity of radiation-induced xerostomia. The results suggest that acupuncture focused in a preventive approach can be a useful therapy in the management of patients with head and neck cancer undergoing RT.

Técnicas de extrações e procedimentos de clean-up para a determinação de hidrocarbonetos policílicos aromáticos (HPA) em sedimentos da costa do Ceará

Extraction and clean-up are essential points in polycyclic aromatic hydrocarbon (PAHs) analysis in a solid matrix. This work compares extraction techniques and clean-up procedures for PAH analysis. PAH levels, their toxicological significance and source were also evaluated in the waters of the Cocó and Ceará rivers. The efficiency of PAH recovery was higher for the soxhlet and ultrasonic techniques. PAH recovery varied from 69.3 to 99.3%. Total PAH concentration (ΣHPA) varied from 720.73 to 2234.76 µg kg-1 (Cocó river) and 96.4 to 1859.21 µg kg-1 (Ceará river). The main PAH sources are pyrolytic processes and the levels were classified as medium so that adverse effects are possible.