Hydrologic modeling and uncertainty analysis of an ungauged watershed using mapwindow-swat

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

Lean construction in rehabilitation works – suitability analysis and contribution for the definition of an implementation model

Proceedings IGLC-19, July 2011, Lima, Perú

Earth-based repair mortars: experimental analysis with different binders and natural fibers

RESTAPIA 2012 - Int. Conf. on Rammed Earth Conservation, Valencia, 21-23 June 2012

Health expenditures in the OECD: A political economy analysis using structural breaks

A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

Constraint reasoning with local search for continuous optimization

Optimization is a very important field for getting the best possible value for the optimization function. Continuous optimization is optimization over real intervals. There are many global and local search techniques. Global search techniques try to get the global optima of the optimization problem. However, local search techniques are used more since they try to find a local minimal solution within an area of the search space. In Continuous Constraint Satisfaction Problems (CCSP)s, constraints are viewed as relations between variables, and the computations are supported by interval analysis. The continuous constraint programming framework provides branch-and-prune algorithms for covering sets of solutions for the constraints with sets of interval boxes which are the Cartesian product of intervals. These algorithms begin with an initial crude cover of the feasible space (the Cartesian product of the initial variable domains) which is recursively refined by interleaving pruning and branching steps until a stopping criterion is satisfied. In this work, we try to find a convenient way to use the advantages in CCSP branchand- prune with local search of global optimization applied locally over each pruned branch of the CCSP. We apply local search techniques of continuous optimization over the pruned boxes outputted by the CCSP techniques. We mainly use steepest descent technique with different characteristics such as penalty calculation and step length. We implement two main different local search algorithms. We use “Procure”, which is a constraint reasoning and global optimization framework, to implement our techniques, then we produce and introduce our results over a set of benchmarks.

Enrichment of a PHA producing microbial community in a continuous bioreactor setup

Polyhydroxyalkanoates (PHAs) are biosynthetic polyesters, biodegradable and biocompatible making them of great interest for industrial purposes. The use of low value substrates with mixed microbial communities (MMC) is a strategy currently used to decrease the elevated PHA production costs. PHA production process requires an important step for selection and enrichment of PHA-storing microorganisms which is usually carried out in a Sequencing Batch Reactor (SBR). The aim of this study was to optimize the PHA accumulating culture selection stage using a 2-stage Continuous Stirrer Tank Reactor (CSTR) system. The system was composed by two separate feast and famine bioreactors operated continuously, mimicking the feast and famine phases in a SBR system. Acetate was used as carbon source and biomass seed was highly enriched in Plasticicumulans acidivorans obtained from activated sludge. The system was operated under two different sets of conditions (setup 1 and 2), maintaining a system total retention time of 12 hours and an OLR of 2.25 Cmmol/L.h-1. An average PHB-content of 3.3 % wt was obtained in setup 1 and 4.8% wt in setup 2. Several other experiments were performed in order to better understand the continuous system behaviour, using biomass from the continuous system. With the fed-batch experiment a maximum of 8.1% PHB was stored and the maximum substrate uptake and specific growth rates obtained in the growth experiment (1.15 Cmol Cmol-1.h-1 and 0.53 Cmol Cmol-1.h-1) were close to the ones from continuous system (1.12 Cmol Cmol-1.h-1 and 0.59 Cmol Cmol-1.h-1). The microbial community was characterized trough microscopic visualization, Denaturing Gradient Gel Electrophoresis (DGGE) analysis and Fluorescent in situ hybridization (FISH). The last studied performed mimicked the continuous system by building up a SBR system with all the same operational conditions while adding an extra acetate dosage during the 12 h cycle, simulating the substrate passing from the feast to the famine reactors under continuous operation. It was shown that possibly the continuous system was not able to efficiently select for PHB storing organisms under the operational conditions imposed, although the selected culture was capable of consuming the substrate and grow fast. This main conclusion might have resulted from two major factors affecting the system performance: the ammonium concentration in the Feast reactor and the amount of substrate leaching from the Feast to the Famine reactor.

Analysis, testing and development of safe cleaning methods of rusted stone material

Three different treatments were applied on several specimens of dolomitic and calcitic marble, properly stained with rust to mimic real situations (the stone specimens were exposed to the natural environment for about six months in contact with rusted iron). Thirty six marble specimens, eighteen calcitic and eighteen dolomitic, were characterized before and after treatment and monitored throughout the cleaning tests. The specimens were characterized by SEM-EDS (Scanning Electron Microscopy coupled with Energy Dispersion System), XRD (XRay Diffraction), XRF (X-Ray Fluorescence), FTIR (Fourier Transform Infrared Spectroscopy) and color measurements. It was also made a microscopic and macroscopic analysis of the stone surface along with the tests of short and long term capillary absorption. A series of test trials were conducted in order to understand which concentrations and contact times best suits to this purpose, to confirm what had been written to date in the literature. We sought to develop new methods of treatment application, skipping the usual methods of applying chemical treatments on stone substrates, with the use of cellulose poultice, resorting to the agar, a gel already used in many other areas, being something new in this area, which possesses great applicability in the field of conservation of stone materials. After the application of the best methodology for cleaning, specimens were characterized again in order to understand which treatment was more effective and less harmful, both for the operator and the stone material. Very briefly conclusions were that for a very intense and deep penetration into the stone, a solution of 3.5% of SDT buffered with ammonium carbonate to pH around 7 applied with agar support would be indicated. For rust stains in its initial state, the use of Ammonium citrate at a concentration of 5% buffered with ammonium to pH 7 could be applied more than once until satisfactory results appear.

Land cover mapping analysis and urban growth modeling using remote sensing techniques

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

Analysis of temporal and spatial variations of forest. A case of study in notheastern Armenia

The forest has a crucial ecological role and the continuous forest loss can cause colossal effects on the environment. As Armenia is one of the low forest covered countries in the world, this problem is more critical. Continuous forest disturbances mainly caused by illegal logging started from the early 1990s had a huge damage on the forest ecosystem by decreasing the forest productivity and making more areas vulnerable to erosion. Another aspect of the Armenian forest is the lack of continuous monitoring and absence of accurate estimation of the level of cuts in some years. In order to have insight about the forest and the disturbances in the long period of time we used Landsat TM/ETM + images. Google Earth Engine JavaScript API was used, which is an online tool enabling the access and analysis of a great amount of satellite imagery. To overcome the data availability problem caused by the gap in the Landsat series in 1988- 1998, extensive cloud cover in the study area and the missing scan lines, we used pixel based compositing for the temporal window of leaf on vegetation (June-late September). Subsequently, pixel based linear regression analyses were performed. Vegetation indices derived from the 10 biannual composites for the years 1984-2014 were used for trend analysis. In order to derive the disturbances only in forests, forest cover layer was aggregated and the original composites were masked. It has been found, that around 23% of forests were disturbed during the study period.

Automated quantitative analysis of MCC-IMS spectra

Ion Mobility Spectrometry coupled with Multi Capillary Columns (MCC -IMS) is a fast analytical technique working at atmospheric pressure with high sensitivity and selectivity making it suitable for the analysis of complex biological matrices. MCC-IMS analysis generates its information through a 3D spectrum with peaks, corresponding to each of the substances detected, providing quantitative and qualitative information. Sometimes peaks of different substances overlap, making the quantification of substances present in the biological matrices a difficult process. In the present work we use peaks of isoprene and acetone as a model for this problem. These two volatile organic compounds (VOCs) that when detected by MCC-IMS produce two overlapping peaks. In this work it’s proposed an algorithm to identify and quantify these two peaks. This algorithm uses image processing techniques to treat the spectra and to detect the position of the peaks, and then fits the data to a custom model in order to separate the peaks. Once the peaks are separated it calculates the contribution of each peak to the data.

Contribution to a strategic plan for the implementation of continuous improvement process in an MRO

This Work Project studies the Continuous Improvement and Processes (CIP) department at TAP Maintenance & Engineering. The project has the objective to provide insights to align the activities of the department with the strategy of the organization. For such, two focuses were taken: (i) an internal analysis which highlighted a need for transversal change to ensure the adoption of Continuous Improvement at TAP, and (ii) a process which outlined objectives and projects to be pursued to prioritize CIP’s activities in accordance with the organization’s goals. The outcome includes (a) important recommendations concerning strategic planning and competition evaluation and (b) a process’ output that reflects a balance among factors influencing the priority of projects.

Analysis of metabolic flux distributions in relation to the extracellular environment in Avian cells

Continuous cell lines that proliferate in chemically defined and simple media have been highly regarded as suitable alternatives for vaccine production. One such cell line is the AG1.CR.pIX avian cell line developed by PROBIOGEN. This cell line can be cultivated in a fully scalable suspension culture and adapted to grow in chemically defined, calf serum free, medium [1]–[5]. The medium composition and cultivation strategy are important factors for reaching high virus titers. In this project, a series of computational methods was used to simulate the cell’s response to different environments. The study is based on the metabolic model of the central metabolism proposed in [1]. In a first step, Metabolic Flux Analysis (MFA) was used along with measured uptake and secretion fluxes to estimate intracellular flux values. The network and data were found to be consistent. In a second step, Flux Balance Analysis (FBA) was performed to access the cell’s biological objective. The objective that resulted in the best predicted results fit to the experimental data was the minimization of oxidative phosphorylation. Employing this objective, in the next step Flux Variability Analysis (FVA) was used to characterize the flux solution space. Furthermore, various scenarios, where a reaction deletion (elimination of the compound from the media) was simulated, were performed and the flux solution space for each scenario was calculated. Growth restrictions caused by essential and non-essential amino acids were accurately predicted. Fluxes related to the essential amino acids uptake and catabolism, the lipid synthesis and ATP production via TCA were found to be essential to exponential growth. Finally, the data gathered during the previous steps were analyzed using principal component analysis (PCA), in order to assess potential changes in the physiological state of the cell. Three metabolic states were found, which correspond to zero, partial and maximum biomass growth rate. Elimination of non-essential amino acids or pyruvate from the media showed no impact on the cell’s assumed normal metabolic state.