Transmission electron tomography: quality assessment and enhancement for three-dimensional imaging of nanostructures

Nanotechnology has revolutionised humanity's capability in building microscopic systems by manipulating materials on a molecular and atomic scale. Nan-osystems are becoming increasingly smaller and more complex from the chemical perspective which increases the demand for microscopic characterisation techniques. Among others, transmission electron microscopy (TEM) is an indispensable tool that is increasingly used to study the structures of nanosystems down to the molecular and atomic scale. However, despite the effectivity of this tool, it can only provide 2-dimensional projection (shadow) images of the 3D structure, leaving the 3-dimensional information hidden which can lead to incomplete or erroneous characterization. One very promising inspection method is Electron Tomography (ET), which is rapidly becoming an important tool to explore the 3D nano-world. ET provides (sub-)nanometer resolution in all three dimensions of the sample under investigation. However, the fidelity of the ET tomogram that is achieved by current ET reconstruction procedures remains a major challenge. This thesis addresses the assessment and advancement of electron tomographic methods to enable high-fidelity three-dimensional investigations. A quality assessment investigation was conducted to provide a quality quantitative analysis of the main established ET reconstruction algorithms and to study the influence of the experimental conditions on the quality of the reconstructed ET tomogram. Regular shaped nanoparticles were used as a ground-truth for this study. It is concluded that the fidelity of the post-reconstruction quantitative analysis and segmentation is limited, mainly by the fidelity of the reconstructed ET tomogram. This motivates the development of an improved tomographic reconstruction process. In this thesis, a novel ET method was proposed, named dictionary learning electron tomography (DLET). DLET is based on the recent mathematical theorem of compressed sensing (CS) which employs the sparsity of ET tomograms to enable accurate reconstruction from undersampled (S)TEM tilt series. DLET learns the sparsifying transform (dictionary) in an adaptive way and reconstructs the tomogram simultaneously from highly undersampled tilt series. In this method, the sparsity is applied on overlapping image patches favouring local structures. Furthermore, the dictionary is adapted to the specific tomogram instance, thereby favouring better sparsity and consequently higher quality reconstructions. The reconstruction algorithm is based on an alternating procedure that learns the sparsifying dictionary and employs it to remove artifacts and noise in one step, and then restores the tomogram data in the other step. Simulation and real ET experiments of several morphologies are performed with a variety of setups. Reconstruction results validate its efficiency in both noiseless and noisy cases and show that it yields an improved reconstruction quality with fast convergence. The proposed method enables the recovery of high-fidelity information without the need to worry about what sparsifying transform to select or whether the images used strictly follow the pre-conditions of a certain transform (e.g. strictly piecewise constant for Total Variation minimisation). This can also avoid artifacts that can be introduced by specific sparsifying transforms (e.g. the staircase artifacts the may result when using Total Variation minimisation). Moreover, this thesis shows how reliable elementally sensitive tomography using EELS is possible with the aid of both appropriate use of Dual electron energy loss spectroscopy (DualEELS) and the DLET compressed sensing algorithm to make the best use of the limited data volume and signal to noise inherent in core-loss electron energy loss spectroscopy (EELS) from nanoparticles of an industrially important material. Taken together, the results presented in this thesis demonstrates how high-fidelity ET reconstructions can be achieved using a compressed sensing approach.

Comparison of five popular normalization methods using a spike-in proteomics data set

Mass spectrometry (MS)-based proteomics has seen significant technical advances during the past two decades and mass spectrometry has become a central tool in many biosciences. Despite the popularity of MS-based methods, the handling of the systematic non-biological variation in the data remains a common problem. This biasing variation can result from several sources ranging from sample handling to differences caused by the instrumentation. Normalization is the procedure which aims to account for this biasing variation and make samples comparable. Many normalization methods commonly used in proteomics have been adapted from the DNA-microarray world. Studies comparing normalization methods with proteomics data sets using some variability measures exist. However, a more thorough comparison looking at the quantitative and qualitative differences of the performance of the different normalization methods and at their ability in preserving the true differential expression signal of proteins, is lacking. In this thesis, several popular and widely used normalization methods (the Linear regression normalization, Local regression normalization, Variance stabilizing normalization, Quantile-normalization, Median central tendency normalization and also variants of some of the forementioned methods), representing different strategies in normalization are being compared and evaluated with a benchmark spike-in proteomics data set. The normalization methods are evaluated in several ways. The performance of the normalization methods is evaluated qualitatively and quantitatively on a global scale and in pairwise comparisons of sample groups. In addition, it is investigated, whether performing the normalization globally on the whole data or pairwise for the comparison pairs examined, affects the performance of the normalization method in normalizing the data and preserving the true differential expression signal. In this thesis, both major and minor differences in the performance of the different normalization methods were found. Also, the way in which the normalization was performed (global normalization of the whole data or pairwise normalization of the comparison pair) affected the performance of some of the methods in pairwise comparisons. Differences among variants of the same methods were also observed.

Knowledge and perceptions of quality of obstetric and newborn care of local health providers: a cross-sectional study in three districts in Malawi

Aim Quality of service delivery for maternal and newborn health in Malawi is influenced by human resource shortages and knowledge and care practices of the existing service providers. We assessed Malawian healthcare providers’ knowledge of management of routine labour, emergency obstetric care and emergency newborn care; correlated knowledge with reported confidence and previous study or training; and measured perception of the care they provided. Methods his study formed part of a large-scale quality of care assessment in three districts (Kasungu, Lilongwe and Salima) of Malawi. Subjects were selected purposively by their role as providers of obstetric and newborn care during routine visits to health facilities by a research assistant. Research assistants introduced and supervised the self-completed questionnaire by the service providers. Respondents included 42 nurse midwives, 1 clinical officer, 4 medical assistants and 5 other staff. Of these, 37 were staff working in facilities providing Basic Emergency Obstetric Care (BEMoC) and 15 were from staff working in facilities providing Comprehensive Emergency Obstetric Care (CEMoC). Results Knowledge regarding management of routine labour was good (80% correct responses), but knowledge of correct monitoring during routine labour (35% correct) was not in keeping with internationally recognized good practice. Questions regarding emergency obstetric care were answered correctly by 70% of respondents with significant variation depending on clinicians’ place of work. Knowledge of emergency newborn care was poor across all groups surveyed with 58% correct responses and high rates of potentially life-threatening responses from BEmOC facilities. Reported confidence and training had little impact on levels of knowledge. Staff in general reported perception of poor quality of care. Conclusion Serious deficiencies in providers’ knowledge regarding monitoring during routine labour and management of emergency newborn care were documented. These may contribute to maternal and neonatal deaths in Malawi. The knowledge gap cannot be overcome by simply providing more training.

An hr-adaptive discontinuous Galerkin method for advection-diffusion problems

We propose an adaptive mesh refinement strategy based on exploiting a combination of a pre-processing mesh re-distribution algorithm employing a harmonic mapping technique, and standard (isotropic) mesh subdivision for discontinuous Galerkin approximations of advection-diffusion problems. Numerical experiments indicate that the resulting adaptive strategy can efficiently reduce the computed discretization error by clustering the nodes in the computational mesh where the analytical solution undergoes rapid variation.

Method of numerical correction of errors occasioned by delay of records during the monitoring of environmental variables of interest for animal production

As condições de ambiente térmico e aéreo, no interior de instalações para animais, alteram-se durante o dia, devido à influência do ambiente externo. Para que análises estatísticas e geoestatísticas sejam representativas, uma grande quantidade de pontos distribuídos espacialmente na área da instalação deve ser monitorada. Este trabalho propõe que a variação no tempo das variáveis ambientais de interesse para a produção animal, monitoradas no interior de instalações para animais, pode ser modelada com precisão a partir de registros discretos no tempo. O objetivo deste trabalho foi desenvolver um método numérico para corrigir as variações temporais dessas variáveis ambientais, transformando os dados para que tais observações independam do tempo gasto durante a aferição. O método proposto aproximou os valores registrados com retardos de tempo aos esperados no exato momento de interesse, caso os dados fossem medidos simultaneamente neste momento em todos os pontos distribuídos espacialmente. O modelo de correção numérica para variáveis ambientais foi validado para o parâmetro ambiental temperatura do ar, sendo que os valores corrigidos pelo método não diferiram pelo teste Tukey, a 5% de probabilidade dos valores reais registrados por meio de dataloggers.

Trade Shocks and Local Labor Markets' Linkages: Theory and Evidence

In the past few years, there has been a concern among economists and policy makers that increased openness to international trade affects some regions in a country more than others. Recent research has found that local labor markets more exposed to import competition through their initial employment composition experience worse outcomes in several dimensions such as, employment, wages, and poverty. Although there is evidence that regions within a country exhibit variation in the intensity with which they trade with each other and with other countries, trade linkages have been ignored in empirical analyses of the regional effects of trade, which focus on differences in employment composition. In this dissertation, I investigate how local labor markets' trade linkages shape the response of wages to international trade shocks. In the second chapter, I lay out a standard multi-sector general equilibrium model of trade, where domestic regions trade with each other and with the rest of the world. Using this benchmark, I decompose a region's wage change resulting from a national import cost shock into a direct effect on prices, holding other endogenous variables constant, and a series of general equilibrium effects. I argue the direct effect provides a natural measure of exposure to import competition within the model since it summarizes the effect of the shock on a region's wage as a function of initial conditions given by its trade linkages. I call my proposed measure linkage exposure while I refer to the measures used in previous studies as employment exposure. My theoretical analysis also shows that the assumptions previous studies make on trade linkages are not consistent with the standard trade model. In the third chapter, I calibrate the model to the Brazilian economy in 1991--at the beginning of a period of trade liberalization--to perform a series of experiments. In each of them, I reduce the Brazilian import cost by 1 percent in a single sector and I calculate how much of the cross-regional variation in counterfactual wage changes is explained by exposure measures. Over this set of experiments, employment exposure explains, for the median sector, 2 percent of the variation in counterfactual wage changes while linkage exposure explains 44 percent. In addition, I propose an estimation strategy that incorporates trade linkages in the analysis of the effects of trade on observed wages. In the model, changes in wages are completely determined by changes in market access, an endogenous variable that summarizes the real demand faced by a region. I show that a linkage measure of exposure is a valid instrument for changes in market access within Brazil. By using observed wage changes in Brazil between 1991-2000, my estimates imply that a region at the 25th percentile of the change in domestic market access induced by trade liberalization, experiences a 0.6 log points larger wage decline (or smaller wage increase) than a region at the 75th percentile. The estimates from a regression of wages changes on exposure imply that a region at the 25th percentile of exposure experiences a 3 log points larger wage decline (or smaller wage increase) than a region at the 75th percentile. I conclude that estimates based on exposure overstate the negative impact of trade liberalization on wages in Brazil. In the fourth chapter, I extend the standard model to allow for two types of workers according to their education levels: skilled and unskilled. I show that there is substantial variation across Brazilian regions in the skill premium. I use the exogenous variation provided by tariff changes to estimate the impact of market access on the skill premium. I find that decreased domestic market access resulting from trade liberalization resulted in a higher skill premium. I propose a mechanism to explain this result: that the manufacturing sector is relatively more intensive in unskilled labor and I show empirical evidence that supports this hypothesis.

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

Comunidades energéticas sustentáveis: estudo de Implementação de uma comunidade eólica no Algarve

Tese de Doutoramento, Gestão da Inovação e do Território, Faculdade de Economia, Universidade do Algarve, 2016

Primeira intervenção da GNR no local do crime

Este trabalho aborda a questão dos atos preparatórios no local do crime, isto é, as medidas cautelares e de polícia que o primeiro interveniente policial que chega ao local deve aplicar. As diligências efetuadas pelo primeiro militar que assume uma ocorrência e que, normalmente, não é especialista na área da Investigação Criminal ou forense, revelam-se de elevada importância para o sucesso da investigação pois repercutem-se ao longo de toda a investigação. Essa abordagem caracteriza-se por não visar uma intervenção investigatória e inspetiva, mas sim de prevenção e proteção do local. O objetivo geral do trabalho consiste numa contribuição para uma exploração mais determinada do local onde foi cometido um crime, através do melhor desempenho possível do primeiro interveniente policial. Os objetivos específicos passam por definir os procedimentos a tomar pelo primeiro interveniente (tendo em conta a sua especialidade, materiais e particularidades da fase da investigação) e definir o que é, para ele, um crime de cenário, identificando as possíveis repercussões de uma má gestão do local do crime para o sucesso da investigação. Utilizamos o método comparativo, estudando os diferentes Manuais de procedimentos (nacionais e internacionais). O quadro de referência é o materialismo histórico pois enfatizamos a dimensão histórica dos processos sociais, a legislação vigente e os problemas atuais para interpretar o nosso estudo. Este trabalho assume contornos exploratório-explicativos. Seguimos um método dedutivo, pois pretende-se chegar a um caso particular da lei geral, ou seja, aos procedimentos específicos do primeiro interveniente policial entre toda a gestão do local do crime. Os resultados mais significativos são a justificação da importância do local do crime para a Investigação Criminal e da complexidade que pode advir para o trabalho do primeiro interveniente. É possível concluir um conjunto padrão de ações que devem ser tomadas (guia prático) e como se pode melhorar a intervenção através de formação e cooperação entre os elementos.

The Effects of Instrumental Touching on Infant Pain Perception and the Effects of Eutectic Mixture of Local Anesthetics (EMLA) on the Reduction of Pain

Background: Premature infants, who have to spend the first week of their lives in neonatal intensive care units (NICUs), experience pain and stress in numerous cases, and they are exposed to many invasive interventions. The studies have shown that uncontrolled pain experienced during early life has negative and long-term side effects, such as distress, and such experiences negatively affect the development of the central nervous system Objectives: The purpose of the study was to examine the effects of touching on infant pain perception and the effects of eutectic mixture of local anesthetic (EMLA) on the reduction of pain. Patients and Methods: Data for the study were collected between March and August 2012 from the neonatal clinic of a university hospital located in eastern Turkey. The population of the study consisted of premature infants who were undergoing treatment, completed the first month and who were approved for Hepatitis B vaccine. The study consisted of two experimental groups and one control group. Information forms, intervention follow-up forms, and Premature Infant Pain Profile (PIPP) were used to collect the data. EMLA cream was applied on the vastus lateralis muscles of the first experimental group before the vaccination. The second experimental group was vaccinated by imitation (placebo), without a needle tip or medicine. Vaccination was carried out using instrumental touch in this group. A routine vaccination was applied in the control group. Results: Mean pain scores of the group to which EMLA was applied were lower in a statistically significant way (P < 0.05) compared to the pain scores of the other groups. Moreover, it was determined that even though invasive intervention was not applied to the newborns, the touching caused them to feel pain just as in the placebo group (P < 0.005). Conclusions: The results demonstrated that EMLA was an effective method for reducing pain in premature newborns, and the use of instrumental touch for invasive intervention stimulated the pain perception in the newborns.

A method for the estimation of potential evapotranspiration and/or open pan evaporation over Brazil.

This paper presents a simple regression model to estimate potential evapotranspiration and/or open pan evaporation data for a wide network of stations in Brazil. The model uses the readily available data sets like geocoordinates (latitude) and precipitation as inputs. Potential evapotranspiration presents a high correlation with the precipitation during summer months and with latitude during winter months. It also shows association with longitude and elevation; the magnitude of variation appears to be very small. This model gave a R2 varying from 0.460 to 0.902 for different months. The model is also extended to weekly periods of individual years ant tested with the open pan evaporation data of Bebedouro and Mandacaru. The agreement between observed and predicted values appears to be good.

Analysis of Land Use Change as a Method of Predicting Water Demands in an Urbanizing Environment: Redland, Miami-Dade County, Florida

The fluctuation in water demand in the Redland community of Miami-Dade County was examined using land use data from 2001 and 2011 and water estimation techniques provided by local and state agencies. The data was converted to 30 m mosaicked raster grids that indicated land use change, and associated water demand measured in gallons per day per acre. The results indicate that, first, despite an increase in population, water demand decreased overall in Redland from 2001 to 2011. Second, conversion of agricultural lands to residential lands actually caused a decrease in water demand in most cases while acquisition of farmland by public agencies also caused a sharp decline. Third, conversion of row crops and groves to nurseries was substantial and resulted in a significant increase in water demand in all such areas converted. Finally, estimating water demand based on land use, rather than population, is a more accurate approach.

An Islanding Detection Method based on Impedance Estimation and Grid Identification for Grid-Tie Distributed Power Generation Systems

Power system policies are broadly on track to escalate the use of renewable energy resources in electric power generation. Integration of dispersed generation to the utility network not only intensifies the benefits of renewable generation but also introduces further advantages such as power quality enhancement and freedom of power generation for the consumers. However, issues arise from the integration of distributed generators to the existing utility grid are as significant as its benefits. The issues are aggravated as the number of grid-connected distributed generators increases. Therefore, power quality demands become stricter to ensure a safe and proper advancement towards the emerging smart grid. In this regard, system protection is the area that is highly affected as the grid-connected distributed generation share in electricity generation increases. Islanding detection, amongst all protection issues, is the most important concern for a power system with high penetration of distributed sources. Islanding occurs when a portion of the distribution network which includes one or more distributed generation units and local loads is disconnected from the remaining portion of the grid. Upon formation of a power island, it remains energized due to the presence of one or more distributed sources. This thesis introduces a new islanding detection technique based on an enhanced multi-layer scheme that shows superior performance over the existing techniques. It provides improved solutions for safety and protection of power systems and distributed sources that are capable of operating in grid-connected mode. The proposed active method offers negligible non-detection zone. It is applicable to micro-grids with a number of distributed generation sources without sacrificing the dynamic response of the system. In addition, the information obtained from the proposed scheme allows for smooth transition to stand-alone operation if required. The proposed technique paves the path towards a comprehensive protection solution for future power networks. The proposed method is converter-resident and all power conversion systems that are operating based on power electronics converters can benefit from this method. The theoretical analysis is presented, and extensive simulation results confirm the validity of the analytical work.

FROM GENES TO GENOMES: LOCAL ADAPTATION AND ADAPTIVE POTENTIAL IN TWO ARCTIC SEABIRDS

By investigating the mechanisms underlying the evolution and the maintenance of local adaptations we can help predict how species will adapt to future environmental change. In this thesis I investigate local adaptation and adaptive potential in thick-billed and common murres (Uria lomvia and U. aalge), two arctic seabirds of international conservation concern. Thanks to the recent development of new genomic methods, I address three major themes that are relevant for both the development of evolutionary theory and conservation: 1) the role of gene flow in the origin and maintenance of adaptation; 2) levels and distribution of standing genetic variation, and their contribution to adaptive potential; and 3) the genomic mechanisms maintaining an adaptive dimorphism within a single interbreeding population. First, I review the literature on genomics of local adaptation with gene flow and find that adaptation can be maintained despite gene flow, that gene flow itself can promote adaptation, and that genetic architecture is important in the origin and maintenance of local adaptations. Second, I genotype genome-wide markers and toll-like receptor genes (TLRs) to investigate local adaptation and adaptive potential in thick-billed murres. Thick-billed murres do not show signatures of local adaptation to their breeding grounds, but outlier loci group birds according to their non-breeding distributions, suggesting that selection and/or demographic connectivity in the winter may explain patterns of differentiation in this species. Genetic variation at TLRs does not decrease with increasing latitude as predicted, but tests of selection and measures of genetic diversity suggest differences in local selective regimes at most genes. Thick-billed murres show high levels of standing genetic variation and their adaptive potential will mostly depend on rate and magnitude of environmental change. Finally, I improve and annotate the assembly of the highly heterozygous genome of the thick-billed murre. Using this assembly as a reference, I perform whole genome analyses to investigate the genomic basis of an adaptive dimorphism in Atlantic common murres. I show for the first time that a 60 kb complex copy number variant in a non-coding region maintains differences in plumage and cold adaptation despite high gene flow.

Characterisation and investigation of local variations in mechanical behaviour in cast aluminium using gradient solidification, Digital Image Correlation and finite element simulation

Due to design and process-related factors, there are local variations in the microstructure and mechanical behaviour of cast components. This work establishes a Digital Image Correlation (DIC) based method for characterisation and investigation of the effects of such local variations on the behaviour of a high pressure, die cast (HPDC) aluminium alloy. Plastic behaviour is studied using gradient solidified samples and characterisation models for the parameters of the Hollomon equation are developed, based on microstructural refinement. Samples with controlled microstructural variations are produced and the observed DIC strain field is compared with Finite Element Method (FEM) simulation results. The results show that the DIC based method can be applied to characterise local mechanical behaviour with high accuracy. The microstructural variations are observed to cause a redistribution of strain during tensile loading. This redistribution of strain can be predicted in the FEM simulation by incorporating local mechanical behaviour using the developed characterization model. A homogeneous FEM simulation is unable to predict the observed behaviour. The results motivate the application of a previously proposed simulation strategy, which is able to predict and incorporate local variations in mechanical behaviour into FEM simulations already in the design process for cast components.