936 resultados para Fauna - Autotoxaemia - Experimental studies


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Over the last several decades, human activities have resulted in environmental changes that have increased the number of stressors that can act on a single environment. In Canadian Shield lakes, two recent stressors, the invasion of Bythotrephes longimanus and calcium decline, have been documented. Widespread acidification of hundreds of North American lakes has resulted in the precipitous decline of lake water calcium concentration. Crustacean zooplankton with high calcium demands are likely to be vulnerable to calcium decline, especially <1.5 mg Ca/L, where survival and reproduction rates are reduced. These taxa are also vulnerable to predation by Bythotrephes that has been implicated in the loss of pelagic biodiversity in soft water lakes. Despite laboratory and field studies aimed at understanding the independent impact of these stressors, it is unclear how their co-occurrence will influence community response. Using a combination of data from a large regional lake survey and field experiments, I examined the individual and joint effects of Bythotrephes and calcium decline on native zooplankton community structure. Results demonstrated that much is known about Bythotrephes and our findings of reduced total zooplankton and species richness, due to the loss of Cladocera, are consistent with field surveys and other experimental studies. While we did not detect strong evidence for an effect of calcium on zooplankton using the lowest calcium concentration among invaded lakes (1.2 mg Ca/L), there is evidence that, as lake water calcium concentrations fall <1 mg Ca/L, per capita growth rates of a broad variety of taxa are expected to decline. At the regional scale, negative effects of Bythotrephes and calcium on abundances of small cladocerans and Daphnia pulicaria, respectively, were in agreement with my experimental observations. We also observed significant interactions between Bythotrephes and calcium for a broad variety of taxa. As Bythotrephes continues to spread and invade lakes that are also declining in aqueous calcium, both stressors are likely to amplify negative effects on Cladocera that appear the most vulnerable. Loss of these important zooplankton in response to both Bythotrephes and calcium decline, is likely to lower zooplankton productivity, with potential effects on phytoplankton and higher trophic levels.

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Numerous studies show that increasing species richness leads to higher ecosystem productivity. This effect is often attributed to more efficient portioning of multiple resources in communities with higher numbers of competing species, indicating the role of resource supply and stoichiometry for biodiversity-ecosystem functioning relationships. Here, we merged theory on ecological stoichiometry with a framework of biodiversity-ecosystem functioning to understand how resource use transfers into primary production. We applied a structural equation model to define patterns of diversity-productivity relationships with respect to available resources. Meta-analysis was used to summarize the findings across ecosystem types ranging from aquatic ecosystems to grasslands and forests. As hypothesized, resource supply increased realized productivity and richness, but we found significant differences between ecosystems and study types. Increased richness was associated with increased productivity, although this effect was not seen in experiments. More even communities had lower productivity, indicating that biomass production is often maintained by a few dominant species, and reduced dominance generally reduced ecosystem productivity. This synthesis, which integrates observational and experimental studies in a variety of ecosystems and geographical regions, exposes common patterns and differences in biodiversity-functioning relationships, and increases the mechanistic understanding of changes in ecosystems productivity.

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Numerous studies show that increasing species richness leads to higher ecosystem productivity. This effect is often attributed to more efficient portioning of multiple resources in communities with higher numbers of competing species, indicating the role of resource supply and stoichiometry for biodiversity-ecosystem functioning relationships. Here, we merged theory on ecological stoichiometry with a framework of biodiversity-ecosystem functioning to understand how resource use transfers into primary production. We applied a structural equation model to define patterns of diversity-productivity relationships with respect to available resources. Meta-analysis was used to summarize the findings across ecosystem types ranging from aquatic ecosystems to grasslands and forests. As hypothesized, resource supply increased realized productivity and richness, but we found significant differences between ecosystems and study types. Increased richness was associated with increased productivity, although this effect was not seen in experiments. More even communities had lower productivity, indicating that biomass production is often maintained by a few dominant species, and reduced dominance generally reduced ecosystem productivity. This synthesis, which integrates observational and experimental studies in a variety of ecosystems and geographical regions, exposes common patterns and differences in biodiversity-functioning relationships, and increases the mechanistic understanding of changes in ecosystems productivity.

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Obestatin is a 23-amino acid C-terminally amidated gastrointestinal peptide derived from preproghrelin and which forms an alpha helix. Although obestatin has a short biological half-life and is rapidly degraded, it is proposed to exert wide-ranging pathophysiological actions. Whilst the precise nature of many of its effects is unclear, accumulating evidence supports positive actions on both metabolism and cardiovascular function. For example, obestatin has been reported to inhibit food and water intake, body weight gain, and gastrointestinal motility, and to also mediate promotion of cell survival and prevention of apoptosis. Obestatin-induced increases in β-cell mass, enhanced adipogenesis and improved lipid metabolism have been noted along with upregulation of genes associated with β-cell regeneration, insulin production and adipogenesis. Furthermore, human circulating obestatin levels generally demonstrate an inverse association with obesity and diabetes, whilst the peptide has been shown to confer protective metabolic effects in experimental diabetes, suggesting that it may hold therapeutic potential in this setting. Obestatin also appears to be involved in blood pressure regulation and to exert beneficial effects on endothelial function, with experimental studies indicating that it may also promote cardioprotective actions against, for example, ischaemia-reperfusion injury. This review will present a critical appraisal of the expanding obestatin research area and discuss the emerging therapeutic potential of this peptide for both metabolic and cardiovascular complications of diabetes. 

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Animal communication plays a crucial role in many species, and it involves a sender producing a signal and a receiver responding to that signal. The shape of a signal is determined by selection pressures acting upon it. One factor that exerts selection on acoustic signals is the acoustic environment through which the signal is transmitted. Recent experimental studies clearly show that senders adjust their signals in response to increased levels of anthropogenic noise. However, to understand how noise affects the whole process of communication, it is vital to know how noise affects the receiver’s response during vocal interactions. Therefore, we experimentally manipulated ambient noise levels to expose male European robins (Erithacus rubecula) to two playback treatments consisting of the same song: one with noise and another one without noise. We found that males responding to a conspecific in a noise polluted environment increased minimum frequency and decreased song complexity and song duration. Thus, we show that the whole process of communication is affected by noise, not just the behaviour of the sender.

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In industrial plants, oil and oil compounds are usually transported by closed pipelines with circular cross-section. The use of radiotracers in oil transport and processing industrial facilities allows calibrating flowmeters, measuring mean residence time in cracking columns, locate points of obstruction or leak in underground ducts, as well as investigating flow behavior or industrial processes such as in distillation towers. Inspection techniques using radiotracers are non-destructive, simple, economic and highly accurate. Among them, Total Count, which uses a small amount of radiotracer with known activity, is acknowledged as an absolute technique for flow rate measurement. A viscous fluid transport system, composed by four PVC pipelines with 13m length (12m horizontal and 1m vertical) and ½, ¾, 1 and 2-inch gauges, respectively, interconnected by maneuvering valves was designed and assembled in order to conduct the research. This system was used to simulate different flow conditions of petroleum compounds and for experimental studies of flow profile in the horizontal and upward directions. As 198Au presents a single photopeak (411,8 keV), it was the radioisotope chosen for oil labeling, in small amounts (6 ml) or around 200 kBq activity, and it was injected in the oil transport lines. A NaI scintillation detector 2”x 2”, with well-defined geometry, was used to measure total activity, determine the calibration factor F and, positioned after a homogenization distance and interconnected to a standardized electronic set of nuclear instrumentation modules (NIM), to detect the radioactive cloud.

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Thesis (Ph.D.)--University of Washington, 2016-08

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In this thesis I experimentally investigate prosocial and ethical behavior in economic interactions. The thesis consists of three experimental research papers that have a broad range of research questions on social responsibility, ignorance and cheating. With these experiments I aim to better understand when and why people behave ethically and/or prosocially and which consequences it has on their own and other players’ payoffs, and on overall efficiency. The results from the three experimental studies suggest that (i) donations to charity by employees are rewarded in an experimental setting, and the effect is driven by reciprocal concerns; (ii) there is a significant fraction of people who decide not to know about negative consequences of own actions, and the sorting of social agents of a low type into ignorance drives self-interested behavior of ignorant agents; and (iii) if the possibility of being exposed as a liar is small, the tendency to lie increases with incentives, indicating that some people have positive and finite costs of lying. Furthermore, when the participants lie, they lie to the full extent, which suggests that the intrinsic cost of lying is fixed.

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Atualmente, no estudo do comportamento de descarregadores de cheias por orifício, é necessário conhecer as pressões ao longo do descarregador, para várias alturas de água na albufeira. Este tipo de estudos tem sido usualmente realizado recorrendo a ensaios experimentais. No entanto, a utilização de modelos numéricos para a simulação do escoamento em estruturas hidráulicas encontra-se numa fase emergente. Neste sentido, a presente dissertação pretende apresentar um estudo numérico relativo ao escoamento em descarregadores de cheias por orifício. Por forma a efetuar o estudo numérico, foi utlizado o programa comercial de CFD FLOW-3D®, reproduzindo um modelo reduzido construído no Laboratório Nacional de Engenharia Civil (LNEC) correspondente a um descarregador por orifício. Para a realização das simulações numéricas foi necessário definir o objeto de estudo, a malha de cálculo, as condições de fronteira e as propriedades do fluido e objeto de modo a reproduzir as situações ensaiadas experimentalmente no LNEC. A proximidade dos resultados experimentais e numéricos para vários níveis de água na albufeira permitiu validar o modelo numérico para este tipo de escoamentos no interior do orifício.

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Numerous studies of the dual-mode scramjet isolator, a critical component in preventing inlet unstart and/or vehicle loss by containing a collection of flow disturbances called a shock train, have been performed since the dual-mode propulsion cycle was introduced in the 1960s. Low momentum corner flow and other three-dimensional effects inherent to rectangular isolators have, however, been largely ignored in experimental studies of the boundary layer separation driven isolator shock train dynamics. Furthermore, the use of two dimensional diagnostic techniques in past works, be it single-perspective line-of-sight schlieren/shadowgraphy or single axis wall pressure measurements, have been unable to resolve the three-dimensional flow features inside the rectangular isolator. These flow characteristics need to be thoroughly understood if robust dual-mode scramjet designs are to be fielded. The work presented in this thesis is focused on experimentally analyzing shock train/boundary layer interactions from multiple perspectives in aspect ratio 1.0, 3.0, and 6.0 rectangular isolators with inflow Mach numbers ranging from 2.4 to 2.7. Secondary steady-state Computational Fluid Dynamics studies are performed to compare to the experimental results and to provide additional perspectives of the flow field. Specific issues that remain unresolved after decades of isolator shock train studies that are addressed in this work include the three-dimensional formation of the isolator shock train front, the spatial and temporal low momentum corner flow separation scales, the transient behavior of shock train/boundary layer interaction at specific coordinates along the isolator's lateral axis, and effects of the rectangular geometry on semi-empirical relations for shock train length prediction. A novel multiplane shadowgraph technique is developed to resolve the structure of the shock train along both the minor and major duct axis simultaneously. It is shown that the shock train front is of a hybrid oblique/normal nature. Initial low momentum corner flow separation spawns the formation of oblique shock planes which interact and proceed toward the center flow region, becoming more normal in the process. The hybrid structure becomes more two-dimensional as aspect ratio is increased but corner flow separation precedes center flow separation on the order of 1 duct height for all aspect ratios considered. Additional instantaneous oil flow surface visualization shows the symmetry of the three-dimensional shock train front around the lower wall centerline. Quantitative synthetic schlieren visualization shows the density gradient magnitude approximately double between the corner oblique and center flow normal structures. Fast response pressure measurements acquired near the corner region of the duct show preliminary separation in the outer regions preceding centerline separation on the order of 2 seconds. Non-intrusive Focusing Schlieren Deflectometry Velocimeter measurements reveal that both shock train oscillation frequency and velocity component decrease as measurements are taken away from centerline and towards the side-wall region, along with confirming the more two dimensional shock train front approximation for higher aspect ratios. An updated modification to Waltrup \& Billig's original semi-empirical shock train length relation for circular ducts based on centerline pressure measurements is introduced to account for rectangular isolator aspect ratio, upstream corner separation length scale, and major- and minor-axis boundary layer momentum thickness asymmetry. The latter is derived both experimentally and computationally and it is shown that the major-axis (side-wall) boundary layer has lower momentum thickness compared to the minor-axis (nozzle bounded) boundary layer, making it more separable. Furthermore, it is shown that the updated correlation drastically improves shock train length prediction capabilities in higher aspect ratio isolators. This thesis suggests that performance analysis of rectangular confined supersonic flow fields can no longer be based on observations and measurements obtained along a single axis alone. Knowledge gained by the work performed in this study will allow for the development of more robust shock train leading edge detection techniques and isolator designs which can greatly mitigate the risk of inlet unstart and/or vehicle loss in flight.

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The role of computer modeling has grown recently to integrate itself as an inseparable tool to experimental studies for the optimization of automotive engines and the development of future fuels. Traditionally, computer models rely on simplified global reaction steps to simulate the combustion and pollutant formation inside the internal combustion engine. With the current interest in advanced combustion modes and injection strategies, this approach depends on arbitrary adjustment of model parameters that could reduce credibility of the predictions. The purpose of this study is to enhance the combustion model of KIVA, a computational fluid dynamics code, by coupling its fluid mechanics solution with detailed kinetic reactions solved by the chemistry solver, CHEMKIN. As a result, an engine-friendly reaction mechanism for n-heptane was selected to simulate diesel oxidation. Each cell in the computational domain is considered as a perfectly-stirred reactor which undergoes adiabatic constant- volume combustion. The model was applied to an ideally-prepared homogeneous- charge compression-ignition combustion (HCCI) and direct injection (DI) diesel combustion. Ignition and combustion results show that the code successfully simulates the premixed HCCI scenario when compared to traditional combustion models. Direct injection cases, on the other hand, do not offer a reliable prediction mainly due to the lack of turbulent-mixing model, inherent in the perfectly-stirred reactor formulation. In addition, the model is sensitive to intake conditions and experimental uncertainties which require implementation of enhanced predictive tools. It is recommended that future improvements consider turbulent-mixing effects as well as optimization techniques to accurately simulate actual in-cylinder process with reduced computational cost. Furthermore, the model requires the extension of existing fuel oxidation mechanisms to include pollutant formation kinetics for emission control studies.

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Terrestrial planets produce crusts as they differentiate. The Earth’s bi-modal crust, with a high-standing granitic continental crust and a low-standing basaltic oceanic crust, is unique in our solar system and links the evolution of the interior and exterior of this planet. Here I present geochemical observations to constrain processes accompanying crustal formation and evolution. My approach includes geochemical analyses, quantitative modeling, and experimental studies. The Archean crustal evolution project represents my perspective on when Earth’s continental crust began forming. In this project, I utilized critical element ratios in sedimentary records to track the evolution of the MgO content in the upper continental crust as a function time. The early Archean subaerial crust had >11 wt. % MgO, whereas by the end of Archean its composition had evolved to about 4 wt. % MgO, suggesting a transition of the upper crust from a basalt-like to a more granite-like bulk composition. Driving this fundamental change of the upper crustal composition is the widespread operation of subduction processes, suggesting the onset of global plate tectonics at ~ 3 Ga (Abstract figure). Three of the chapters in this dissertation leverage the use of Eu anomalies to track the recycling of crustal materials back into the mantle, where Eu anomaly is a sensitive measure of the element’s behavior relative to neighboring lanthanoids (Sm and Gd) during crustal differentiation. My compilation of Sm-Eu-Gd data for the continental crust shows that the average crust has a net negative Eu anomaly. This result requires recycling of Eu-enriched lower continental crust to the mantle. Mass balance calculations require that about three times the mass of the modern continental crust was returned into the mantle over Earth history, possibly via density-driven recycling. High precision measurements of Eu/Eu* in selected primitive glasses of mid-ocean ridge basalt (MORB) from global MORs, combined with numerical modeling, suggests that the recycled lower crustal materials are not found within the MORB source and may have at least partially sank into the lower mantle where they can be sampled by hot spot volcanoes. The Lesser Antilles Li isotope project provides insights into the Li systematics of this young island arc, a representative section of proto-continental crust. Martinique Island lavas, to my knowledge, represent the only clear case in which crustal Li is recycled back into their mantle source, as documented by the isotopically light Li isotopes in Lesser Antilles sediments that feed into the fore arc subduction trench. By corollary, the mantle-like Li signal in global arc lavas is likely the result of broadly similar Li isotopic compositions between the upper mantle and bulk subducting sediments in most arcs. My PhD project on Li diffusion mechanism in zircon is being carried out in extensive collaboration with multiple institutes and employs analytical, experimental and modeling studies. This ongoing project, finds that REE and Y play an important role in controlling Li diffusion in natural zircons, with Li partially coupling to REE and Y to maintain charge balance. Access to state-of-art instrumentation presented critical opportunities to identify the mechanisms that cause elemental fractionation during laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) analysis. My work here elucidates the elemental fractionation associated with plasma plume condensation during laser ablation and particle-ion conversion in the ICP.

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Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

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Frustrated systems, typically characterized by competing interactions that cannot all be simultaneously satisfied, are ubiquitous in nature and display many rich phenomena and novel physics. Artificial spin ices (ASIs), arrays of lithographically patterned Ising-like single-domain magnetic nanostructures, are highly tunable systems that have proven to be a novel method for studying the effects of frustration and associated properties. The strength and nature of the frustrated interactions between individual magnets are readily tuned by design and the exact microstate of the system can be determined by a variety of characterization techniques. Recently, thermal activation of ASI systems has been demonstrated, introducing the spontaneous reversal of individual magnets and allowing for new explorations of novel phase transitions and phenomena using these systems. In this work, we introduce a new, robust material with favorable magnetic properties for studying thermally active ASI and use it to investigate a variety of ASI geometries. We reproduce previously reported perfect ground-state ordering in the square geometry and present studies of the kagome lattice showing the highest yet degree of ordering observed in this fully frustrated system. We consider theoretical predictions of long-range order in ASI and use both our experimental studies and kinetic Monte Carlo simulations to evaluate these predictions. Next, we introduce controlled topological defects into our square ASI samples and observe a new, extended frustration effect of the system. When we introduce a dislocation into the lattice, we still see large domains of ground-state order, but, in every sample, a domain wall containing higher energy spin arrangements originates from the dislocation, resolving a discontinuity in the ground-state order parameter. Locally, the magnets are unfrustrated, but frustration of the lattice persists due to its topology. We demonstrate the first direct imaging of spin configurations resulting from topological frustration in any system and make predictions on how dislocations could affect properties in numerous materials systems.

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Simultaneous Localization and Mapping (SLAM) is a procedure used to determine the location of a mobile vehicle in an unknown environment, while constructing a map of the unknown environment at the same time. Mobile platforms, which make use of SLAM algorithms, have industrial applications in autonomous maintenance, such as the inspection of flaws and defects in oil pipelines and storage tanks. A typical SLAM consists of four main components, namely, experimental setup (data gathering), vehicle pose estimation, feature extraction, and filtering. Feature extraction is the process of realizing significant features from the unknown environment such as corners, edges, walls, and interior features. In this work, an original feature extraction algorithm specific to distance measurements obtained through SONAR sensor data is presented. This algorithm has been constructed by combining the SONAR Salient Feature Extraction Algorithm and the Triangulation Hough Based Fusion with point-in-polygon detection. The reconstructed maps obtained through simulations and experimental data with the fusion algorithm are compared to the maps obtained with existing feature extraction algorithms. Based on the results obtained, it is suggested that the proposed algorithm can be employed as an option for data obtained from SONAR sensors in environment, where other forms of sensing are not viable. The algorithm fusion for feature extraction requires the vehicle pose estimation as an input, which is obtained from a vehicle pose estimation model. For the vehicle pose estimation, the author uses sensor integration to estimate the pose of the mobile vehicle. Different combinations of these sensors are studied (e.g., encoder, gyroscope, or encoder and gyroscope). The different sensor fusion techniques for the pose estimation are experimentally studied and compared. The vehicle pose estimation model, which produces the least amount of error, is used to generate inputs for the feature extraction algorithm fusion. In the experimental studies, two different environmental configurations are used, one without interior features and another one with two interior features. Numerical and experimental findings are discussed. Finally, the SLAM algorithm is implemented along with the algorithms for feature extraction and vehicle pose estimation. Three different cases are experimentally studied, with the floor of the environment intentionally altered to induce slipping. Results obtained for implementations with and without SLAM are compared and discussed. The present work represents a step towards the realization of autonomous inspection platforms for performing concurrent localization and mapping in harsh environments.