Non-invasive monitoring of changes in exhaled markers of airway inflammation in Thoroughbred racehorses

Exhaled breath (EB) and exhaled breath condensate (EBC) contain numerous volatile gases and a wide-array of non-volatile compounds, several of which have been investigated as markers of lower airway inflammation in human and veterinary medicine and have been used to diagnose and monitor diseases associated with pulmonary inflammation. The identification of reliable biomarkers within EB and EBC is an active research focus with the common goal of establishing non-invasive and repeatable assessment of respiratory health and disease in mammals. The application of EB and EBC analysis holds considerable appeal in the investigation of respiratory disease in Thoroughbred racehorses, as inflammatory airway disease (IAD) is a common cause for poor performance in this population of animals. This study documented that EB and EBC samples can be safely collected from Thoroughbred racehorses in their own environment, without adverse effect or interference with the horse’s training regimen. The use of off-line collection and analysis of exhaled gases via chemiluminescence is suitable for the measurement of exhaled carbon monoxide, but is not appropriate for analyzing exhaled nitric oxide in horses. Significant changes in the concentration of exhaled CO and the pH of EBC occurred in response to strenuous exercise and when exercising in different environmental temperatures. Exhaled CO was associated with tracheal mucus score (and the number of neutrophils in the mucus) and EBC pH was significantly different in horses with evidence of neutrophilic IAD compared to horses without IAD. Numerous physiological and environmental variables were identified as confounding factors in the assessment of both exhaled CO and EBC pH, with respiratory rate prior to EB collection, and during EBC collection, consistently identified as an explanatory variable influencing the concentration of exhaled biomarkers. Further studies in EB and EBC analysis in horses need to focus on objectively accounting for key respiratory dynamics during sample collection.

In situ characterization of sediment oxygen demand across the spectrum of non-resuspension to full resuspension with varying bed shear stress

Sediment oxygen demand (SOD) can be a significant oxygen sink in various types of water bodies, particularly slow-moving waters with substantial organic sediment accumulation. In most settings where SOD is a concern, the prevailing hydraulic conditions are such that the impact of sediment resuspension on SOD is not considered. However, in the case of Bubbly Creek in Chicago, Illinois, the prevailing slack water conditions are interrupted by infrequent intervals of very high flow rates associated with pumped combined sewer overflow (CSO) during intense hydrologic events. These events can cause resuspension of the highly organic, nutrient-rich bottom sediments, resulting in precipitous drawdown of dissolved oxygen (DO) in the water column. While many past studies have addressed the dependence of SOD on near-bed velocity and bed shear stress prior to the point of sediment resuspension, there has been limited research that has attempted to characterize the complex and dynamic phenomenon of resuspended-sediment oxygen demand. To address this issue, a new in situ experimental apparatus referred to as the U of I Hydrodynamic SOD Sampler was designed to achieve a broad range of velocities and associated bed shear stresses. This allowed SOD to be analyzed across the spectrum of no sediment resuspension associated with low velocity/ bed shear stress through full sediment resuspension associated with high velocity / bed shear stress. The current study split SOD into two separate components: (1) SODNR is the sediment oxygen demand associated with non-resuspension conditions and is a surface sink calculated using traditional methods to yield a value with units (g/m2/day); and (2) SODR is the oxygen demand associated with resuspension conditions, which is a volumetric sink most accurately characterized using non-traditional methods and units that reflect suspension in the water column (mg/L/day). In the case of resuspension, the suspended sediment concentration was analyzed as a function of bed shear stress, and a formulation was developed to characterize SODR as a function of suspended sediment concentration in a form similar to first-order biochemical oxygen demand (BOD) kinetics with Monod DO term. The results obtained are intended to be implemented into a numerical model containing hydrodynamic, sediment transport, and water quality components to yield oxygen demand varying in both space and time for specific flow events. Such implementation will allow evaluation of proposed Bubbly Creek water quality improvement alternatives which take into account the impact of SOD under various flow conditions. Although the findings were based on experiments specific to the conditions in Bubbly Creek, the techniques and formulations developed in this study should be applicable to similar sites.

The influence of nano-scale second-phase particles on deformation of fine grained calcite mylonites

Grey and white carbonate mylonites were collected along thrust planes of the Helvetic Alps. They are characterised by very small grain sizes and non-random grain shape (SPO) and crystallographic preferred orientation (CPO). Presumably they deformed in the field of grain size sensitive flow by recrystallisation accommodated intracrystalline deformation in combination with granular flow. Both mylonites show a similar mean grain size, but in the grey mylonites the grain size range is larger, the grain shapes are more elongate and the dynamically recrystallised calcite grains are more often twinned. Grey mylonites have an oblique CPO, while the CPO in white mylonites is symmetric with respect to the shear plane. Combustion analysis and TEM investigations revealed that grey mylonites contain a higher amount of highly structured kerogens with particle sizes of a few tens of nanometers, which are finely dispersed at the grain boundaries. During deformation of the rock, nano-scale particles reduced the migration velocity of grain boundaries by Zener drag resulting in slower recrystallisation rates of the calcite aggregate. In the grey mylonites, more strain increments were accommodated by individual grains before they became refreshed by dynamic recrystallisation than in white mylonites, where grain boundary migration was less hindered and recrystallisation cycles were faster. Consequently, grey mylonites represent ‘deformation’ microfabrics while white mylonites are characterised by ‘recrystallisation’ microfabrics. Field geologists must utilise this different deformation behavior when applying the obliquity in CPO and SPO of the respective mylonites as reliable shear sense indicators.

Calibration and simulations of SIXS-P's response to energetic particles

The Solar Intensity X-ray and particle Spectrometer (SIXS) on board BepiColombo's Mercury Planetary Orbiter (MPO) will study solar energetic particles moving towards Mercury and solar X-rays on the dayside of Mercury. The SIXS instrument consists of two detector sub-systems; X-ray detector SIXS-X and particle detector SIXS-P. The SIXS-P subdetector will detect solar energetic electrons and protons in a broad energy range using a particle telescope approach with five outer Si detectors around a central CsI(Tl) scintillator. The measurements made by the SIXS instrument are necessary for other instruments on board the spacecraft. SIXS data will be used to study the Solar X-ray corona, solar flares, solar energetic particles, the Hermean magnetosphere, and solar eruptions. The SIXS-P detector was calibrated by comparing experimental measurement data from the instrument with Geant4 simulation data. Calibration curves were produced for the different side detectors and the core scintillator for electrons and protons, respectively. The side detector energy response was found to be linear for both electrons and protons. The core scintillator energy response to protons was found to be non-linear. The core scintillator calibration for electrons was omitted due to insufficient experimental data. The electron and proton acceptance of the SIXS-P detector was determined with Geant4 simulations. Electron and proton energy channels are clean in the main energy range of the instrument. At higher energies, protons and electrons produce non-ideal response in the energy channels. Due to the limited bandwidth of the spacecraft's telemetry, the particle measurements made by SIXS-P have to be pre-processed in the data processing unit of the SIXS instrument. A lookup table was created for the pre-processing of data with Geant4 simulations, and the ability of the lookup table to provide spectral information from a simulated electron event was analysed. The lookup table produces clean electron and proton channels and is able to separate protons and electrons. Based on a simulated solar energetic electron event, the incident electron spectrum cannot be determined from channel particle counts with a standard analysis method.

Application of chitosan loaded with metal oxide nano particles to remove lead present from sea water

Chitosan is a natural polymer obtained by deacetylation of chitin. After cellulose chitin is the second most abundant polysaccharide in nature. It is biologically safe, non-toxic, biocompatible and biodegradable polysaccharide. Chitosan loaded with zinc oxide nanoparticles have gained more attention bio sorbent because of their better stability, low toxicity, simple and mild preparation method and high sorption capacity. Chitosan loaded with zinc oxide nanoparticles have been prepared of chitosan. The physicochemical properties of nanoparticles were characterized by Fourier Transform Infrared (FTIR), Scanning Electron Microscope (SEM) Analysis. Its sorption capacity for lead and cadmium ions studied. Factors such as initial concentration of lead ions, cadmium ions sorbent amount, contact time, pH and temperature were investigated. It is found that chitosan loaded with zinc oxide nanoparticles could sorb lead and cadmium ions effectively, this sorption rate was affected significantly by initial concentration of lead and cadmium ions, sorbent amount, contact time, pH of solution. The maximum of percentage of lead sorption was 98 % with initial concentration 3 mg/l and sorbent amount 0.05 g, pH 11 in 45 min and cadmiumwas90 %with initial concentration 3mg/l and sorbent amount 0.05 g, pH 11 in45 min. Consequently chitosan loaded with zinc oxide nanoparticles demonstrated greater fixation ability for lead ions than cadmium ions.

Non-inclusion complexes between riboflavin and cyclodextrins

Objectives To investigate the molecular interaction between beta-cyclodextrin (beta CD) or hydroxypropyl-beta-cyclodextrin (HP beta CD) and riboflavin (RF), and to test the anticancer potential of these formulations. Methods The physicochemical characterization of the association between RF and CDs was performed by UV-vis absorption, fluorescence, differential scanning calorimetry and NMR techniques. Molecular dynamics simulation was used to shed light on the mechanism of interaction of RF and CDs. Additionally, in-vitro cell culture tests were performed to evaluate the cytotoxicity of the RFCD complexes against prostate cancer cells. Key findings Neither beta CD nor HP beta CD led to substantial changes in the physicochemical properties of RF (with the exception of solubility). Additionally, rotating frame Overhauser effect spectroscopy experiments detected no spatial correlations between hydrogens from the internal cavity of CDs and RF, while molecular dynamics simulations revealed out-of-ring RFCD interactions. Notwithstanding, both RF beta CD and RFHP beta CD complexes were cytotoxic to PC3 prostate cancer cells. Conclusions The interaction between RF and either beta CD or HP beta CD, at low concentrations, seems to be made through hydrogen bonding between the flavonoid and the external rim of both CDs. Regardless of the mechanism of complexation, our findings indicate that RFCD complexes significantly increase RF solubility and potentiate its antitumour effect.

Large-scale neural dynamics: simple and complex

We review the use of neural field models for modelling the brain at the large scales necessary for interpreting EEG, fMRI, MEG and optical imaging data. Albeit a framework that is limited to coarse-grained or mean-field activity, neural field models provide a framework for unifying data from different imaging modalities. Starting with a description of neural mass models we build to spatially extended cortical models of layered two-dimensional sheets with long range axonal connections mediating synaptic interactions. Reformulations of the fundamental non-local mathematical model in terms of more familiar local differential (brain wave) equations are described. Techniques for the analysis of such models, including how to determine the onset of spatio-temporal pattern forming instabilities, are reviewed. Extensions of the basic formalism to treat refractoriness, adaptive feedback and inhomogeneous connectivity are described along with open challenges for the development of multi-scale models that can integrate macroscopic models at large spatial scales with models at the microscopic scale.

A systems approach to cardiovascular health and disease with a focus on aortic wave dynamics

Cardiovascular diseases (CVDs) have reached an epidemic proportion in the US and worldwide with serious consequences in terms of human suffering and economic impact. More than one third of American adults are suffering from CVDs. The total direct and indirect costs of CVDs are more than $500 billion per year. Therefore, there is an urgent need to develop noninvasive diagnostics methods, to design minimally invasive assist devices, and to develop economical and easy-to-use monitoring systems for cardiovascular diseases. In order to achieve these goals, it is necessary to gain a better understanding of the subsystems that constitute the cardiovascular system. The aorta is one of these subsystems whose role in cardiovascular functioning has been underestimated. Traditionally, the aorta and its branches have been viewed as resistive conduits connected to an active pump (left ventricle of the heart). However, this perception fails to explain many observed physiological results. My goal in this thesis is to demonstrate the subtle but important role of the aorta as a system, with focus on the wave dynamics in the aorta.

The operation of a healthy heart is based on an optimized balance between its pumping characteristics and the hemodynamics of the aorta and vascular branches. The delicate balance between the aorta and heart can be impaired due to aging, smoking, or disease. The heart generates pulsatile flow that produces pressure and flow waves as it enters into the compliant aorta. These aortic waves propagate and reflect from reflection sites (bifurcations and tapering). They can act constructively and assist the blood circulation. However, they may act destructively, promoting diseases or initiating sudden cardiac death. These waves also carry information about the diseases of the heart, vascular disease, and coupling of heart and aorta. In order to elucidate the role of the aorta as a dynamic system, the interplay between the dominant wave dynamic parameters is investigated in this study. These parameters are heart rate, aortic compliance (wave speed), and locations of reflection sites. Both computational and experimental approaches have been used in this research. In some cases, the results are further explained using theoretical models.

The main findings of this study are as follows: (i) developing a physiologically realistic outflow boundary condition for blood flow modeling in a compliant vasculature; (ii) demonstrating that pulse pressure as a single index cannot predict the true level of pulsatile workload on the left ventricle; (iii) proving that there is an optimum heart rate in which the pulsatile workload of the heart is minimized and that the optimum heart rate shifts to a higher value as aortic rigidity increases; (iv) introducing a simple bio-inspired device for correction and optimization of aortic wave reflection that reduces the workload on the heart; (v) deriving a non-dimensional number that can predict the optimum wave dynamic state in a mammalian cardiovascular system; (vi) demonstrating that waves can create a pumping effect in the aorta; (vii) introducing a system parameter and a new medical index, Intrinsic Frequency, that can be used for noninvasive diagnosis of heart and vascular diseases; and (viii) proposing a new medical hypothesis for sudden cardiac death in young athletes.

Guided Migration and Collective Behavior: Cell Dynamics during Cancer Progression

This dissertation focuses on gaining understanding of cell migration and collective behavior through a combination of experiment, analysis, and modeling techniques. Cell migration is a ubiquitous process that plays an important role during embryonic development and wound healing as well as in diseases like cancer, which is a particular focus of this work. As cancer cells become increasingly malignant, they acquire the ability to migrate away from the primary tumor and spread throughout the body to form metastatic tumors. During this process, changes in gene expression and the surrounding tumor environment can lead to changes in cell migration characteristics. In this thesis, I analyze how cells are guided by the texture of their environment and how cells cooperate with their neighbors to move collectively. The emergent properties of collectively moving groups are a particular focus of this work as collective cell dynamics are known to change in diseases such as cancer. The internal machinery for cell migration involves polymerization of the actin cytoskeleton to create protrusions that---in coordination with retraction of the rear of the cell---lead to cell motion. This actin machinery has been previously shown to respond to the topography of the surrounding surface, leading to guided migration of amoeboid cells. Here we show that epithelial cells on nanoscale ridge structures also show changes in the morphology of their cytoskeletons; actin is found to align with the ridge structures. The migration of the cells is also guided preferentially along the ridge length. These ridge structures are on length scales similar to those found in tumor microenvironments and as such provide a system for studying the response of the cells' internal migration machinery to physiologically relevant topographical cues. In addition to sensing surface topography, individual cells can also be influenced by the pushing and pulling of neighboring cells. The emergent properties of collectively migrating cells show interesting dynamics and are relevant for cancer progression, but have been less studied than the motion of individual cells. We use Particle Image Velocimetry (PIV) to extract the motion of a collectively migrating cell sheet from time lapse images. The resulting flow fields allow us to analyze collective behavior over multiple length and time scales. To analyze the connection between individual cell properties and collective migration behavior, we compare experimental flow fields with the migration of simulated cell groups. Our collective migration metrics allow for a quantitative comparison between experimental and simulated results. This comparison shows that tissue-scale decreases in collective behavior can result from changes in individual cell activity without the need to postulate the existence of subpopulations of leader cells or global gradients. In addition to tissue-scale trends in collective behavior, the migration of cell groups includes localized dynamic features such as cell rearrangements. An individual cell may smoothly follow the motion of its neighbors (affine motion) or move in a more individualistic manner (non-affine motion). By decomposing individual motion into both affine and non-affine components, we measure cell rearrangements within a collective sheet. Finally, finite-time Lyapunov exponent (FTLE) values capture the stretching of the flow field and reflect its chaotic character. Applying collective migration analysis techniques to experimental data on both malignant and non-malignant human breast epithelial cells reveals differences in collective behavior that are not found from analyzing migration speeds alone. Non-malignant cells show increased cooperative motion on long time scales whereas malignant cells remain uncooperative as time progresses. Combining multiple analysis techniques also shows that these two cell types differ in their response to a perturbation of cell-cell adhesion through the molecule E-cadherin. Non-malignant MCF10A cells use E-cadherin for short time coordination of collective motion, yet even with decreased E-cadherin expression, the cells remain coordinated over long time scales. In contrast, the migration behavior of malignant and invasive MCF10CA1a cells, which already shows decreased collective dynamics on both time scales, is insensitive to the change in E-cadherin expression.

Effects of Drive Speed Modulation on Dynamics of Slender Rotating Structures

Slender rotating structures are used in many mechanical systems. These structures can suffer from undesired vibrations that can affect the components and safety of a system. Furthermore, since some these structures can operate in a harsh environment, installation and operation of sensors that are needed for closed-loop and collocated control schemes may not be feasible. Hence, the need for an open-loop non-collocated scheme for control of the dynamics of these structures. In this work, the effects of drive speed modulation on the dynamics of slender rotating structures are studied. Slender rotating structures are a type of mechanical rotating structures, whose length to diameter ratio is large. For these structures, the torsion mode natural frequencies can be low. In particular, for isotropic structures, the first few torsion mode frequencies can be of the same order as the first few bending mode frequencies. These situations can be conducive for energy transfer amongst bending and torsion modes. Scenarios with torsional vibrations experienced by rotating structures with continuous rotor-stator contact occur in many rotating mechanical systems. Drill strings used in the oil and gas industry are an example of rotating structures whose torsional vibrations can be deleterious to the components of the drilling system. As a novel approach to mitigate undesired vibrations, the effects of adding a sinusoidal excitation to the rotation speed of a drill string are studied. A portion of the drill string located within a borewell is considered and this rotating structure has been modeled as an extended Jeffcott rotor and a sinusoidal excitation has been added to the drive speed of the rotor. After constructing a three-degree-of-freedom model to capture lateral and torsional motions, the equations of motions are reduced to a single differential equation governing torsional vibrations during continuous stator contact. An approximate solution has been obtained by making use of the Method of Direct Partition of Motions with the governing torsional equation of motion. The results showed that for a rotor undergoing forward or backward whirling, the addition of sinusoidal excitation to the drive speed can cause an increase in the equivalent torsional stiffness, smooth the discontinuous friction force at contact, and reduce the regions of negative slope in the friction coefficient variation with respect to speed. Experiments with a scaled drill string apparatus have also been conducted and the experimental results show good agreement with the numerical results obtained from the developed models. These findings suggest that the extended Jeffcott rotordynamics model can be useful for studies of rotor dynamics in situations with continuous rotor-stator contact. Furthermore, the results obtained suggest that the drive speed modulation scheme can have value for attenuating drill-string vibrations.

Guided Migration and Collective Behavior: Cell Dynamics during Cancer Progression

This dissertation focuses on gaining understanding of cell migration and collective behavior through a combination of experiment, analysis, and modeling techniques. Cell migration is a ubiquitous process that plays an important role during embryonic development and wound healing as well as in diseases like cancer, which is a particular focus of this work. As cancer cells become increasingly malignant, they acquire the ability to migrate away from the primary tumor and spread throughout the body to form metastatic tumors. During this process, changes in gene expression and the surrounding tumor environment can lead to changes in cell migration characteristics. In this thesis, I analyze how cells are guided by the texture of their environment and how cells cooperate with their neighbors to move collectively. The emergent properties of collectively moving groups are a particular focus of this work as collective cell dynamics are known to change in diseases such as cancer. The internal machinery for cell migration involves polymerization of the actin cytoskeleton to create protrusions that---in coordination with retraction of the rear of the cell---lead to cell motion. This actin machinery has been previously shown to respond to the topography of the surrounding surface, leading to guided migration of amoeboid cells. Here we show that epithelial cells on nanoscale ridge structures also show changes in the morphology of their cytoskeletons; actin is found to align with the ridge structures. The migration of the cells is also guided preferentially along the ridge length. These ridge structures are on length scales similar to those found in tumor microenvironments and as such provide a system for studying the response of the cells' internal migration machinery to physiologically relevant topographical cues. In addition to sensing surface topography, individual cells can also be influenced by the pushing and pulling of neighboring cells. The emergent properties of collectively migrating cells show interesting dynamics and are relevant for cancer progression, but have been less studied than the motion of individual cells. We use Particle Image Velocimetry (PIV) to extract the motion of a collectively migrating cell sheet from time lapse images. The resulting flow fields allow us to analyze collective behavior over multiple length and time scales. To analyze the connection between individual cell properties and collective migration behavior, we compare experimental flow fields with the migration of simulated cell groups. Our collective migration metrics allow for a quantitative comparison between experimental and simulated results. This comparison shows that tissue-scale decreases in collective behavior can result from changes in individual cell activity without the need to postulate the existence of subpopulations of leader cells or global gradients. In addition to tissue-scale trends in collective behavior, the migration of cell groups includes localized dynamic features such as cell rearrangements. An individual cell may smoothly follow the motion of its neighbors (affine motion) or move in a more individualistic manner (non-affine motion). By decomposing individual motion into both affine and non-affine components, we measure cell rearrangements within a collective sheet. Finally, finite-time Lyapunov exponent (FTLE) values capture the stretching of the flow field and reflect its chaotic character. Applying collective migration analysis techniques to experimental data on both malignant and non-malignant human breast epithelial cells reveals differences in collective behavior that are not found from analyzing migration speeds alone. Non-malignant cells show increased cooperative motion on long time scales whereas malignant cells remain uncooperative as time progresses. Combining multiple analysis techniques also shows that these two cell types differ in their response to a perturbation of cell-cell adhesion through the molecule E-cadherin. Non-malignant MCF10A cells use E-cadherin for short time coordination of collective motion, yet even with decreased E-cadherin expression, the cells remain coordinated over long time scales. In contrast, the migration behavior of malignant and invasive MCF10CA1a cells, which already shows decreased collective dynamics on both time scales, is insensitive to the change in E-cadherin expression.

Innovation dynamics in rural areas: contributions to capture and measure innovation, valuing territorial specificities

Doutoramento em Gestão Interdisciplinar da Paisagem - Instituto Superior de Agronomia / Universidade dos Açores / Universidade de Évora

Dynamics of Granular Crystals with Elastic-Plastic Contacts

We study the behavior of granular crystals subjected to impact loading that creates plastic deformation at the contacts between constituent particles. Granular crystals are highly periodic arrangements of spherical particles, arranged into densely packed structures resembling crystals. This special class of granular materials has been shown to have unique dynamics with suggested applications in impact protection. However, previous work has focused on very low amplitude impacts where every contact point can be described using the Hertzian contact law, valid only for purely elastic deformation. In this thesis, we extend previous investigation of the dynamics of granular crystals to significantly higher impact energies more suitable for the majority of applications. Additionally, we demonstrate new properties specific to elastic-plastic granular crystals and discuss their potential applications as well. We first develop a new contact law to describe the interaction between particles for large amplitude compression of elastic-plastic spherical particles including a formulation for strain-rate dependent plasticity. We numerically and experimentally demonstrate the applicability of this contact law to a variety of materials typically used in granular crystals. We then extend our investigation to one-dimensional chains of elastic-plastic particles, including chains of alternating dissimilar materials. We show that, using the new elastic-plastic contact law, we can predict the speed at which impact waves with plastic dissipation propagate based on the material properties of the constituent particles. Finally, we experimentally and numerically investigate the dynamics of two-dimensional and three-dimensional granular crystals with elastic-plastic contacts. We first show that the predicted wave speeds for 1D granular crystals can be extended to 2D and 3D materials. We then investigate the behavior of waves propagating across oblique interfaces of dissimilar particles. We show that the character of the refracted wave can be predicted using an analog to Snell's law for elastic-plastic granular crystals and ultimately show how it can be used to design impact guiding "lenses" for mitigation applications.

OC-OT-LIBS: A novel approach to the chemical characterization of single particles

Spectral identification of individual micro- and nano-sized particles by the sequential intervention of optical catapulting, optical trapping and laser-induced breakdown spectroscopy is presented [1]. The three techniques are used for different purposes. Optical catapulting (OC) serves to put the particulate material under inspection in aerosol form [2-4]. Optical trapping (OT) permits the isolation and manipulation of individual particles from the aerosol, which are subsequently analyzed by laser-induced breakdown spectroscopy (LIBS). Once catapulted, the dynamics of particle trapping depends on the laser beam characteristics (power and intensity gradient) and on the particle properties (size, mass and shape). Particles are stably trapped in air at atmospheric pressure and can be conveniently manipulated for a precise positioning for LIBS analysis. The spectra acquired from the individually trapped particles permit a straightforward identification of the inspected material. The current work focuses on the development of a procedure for simultaneously acquiring dual information about the particle under study via LIBS and time-resolved plasma images by taking advantage of the aforementioned features of the OC-OT-LIBS instrument to align the multiple lines in a simple yet highly accurate way. The plasma imaging does not only further reinforce the spectral data, but also allows a better comprehension of the chemical and physical processes involved during laser-particle interaction. Also, a thorough determination of the optimal excitation conditions generating the most information out of each laser event was run along the determination of parameters such as the width of the optical trap, its stability as a function of the laser power and the laser wavelength. The extreme sensibility of the presented OC-OT-LIBS technology allows a detection power of attograms for single/individual particle analysis.

Disorder driven transitions in non-equilibrium quantum systems

This thesis presents studies of the role of disorder in non-equilibrium quantum systems. The quantum states relevant to dynamics in these systems are very different from the ground state of the Hamiltonian. Two distinct systems are studied, (i) periodically driven Hamiltonians in two dimensions, and (ii) electrons in a one-dimensional lattice with power-law decaying hopping amplitudes. In the first system, the novel phases that are induced from the interplay of periodic driving, topology and disorder are studied. In the second system, the Anderson transition in all the eigenstates of the Hamiltonian are studied, as a function of the power-law exponent of the hopping amplitude.

In periodically driven systems the study focuses on the effect of disorder in the nature of the topology of the steady states. First, we investigate the robustness to disorder of Floquet topological insulators (FTIs) occurring in semiconductor quantum wells. Such FTIs are generated by resonantly driving a transition between the valence and conduction band. We show that when disorder is added, the topological nature of such FTIs persists as long as there is a gap at the resonant quasienergy. For strong enough disorder, this gap closes and all the states become localized as the system undergoes a transition to a trivial insulator.

Interestingly, the effects of disorder are not necessarily adverse, disorder can also induce a transition from a trivial to a topological system, thereby establishing a Floquet Topological Anderson Insulator (FTAI). Such a state would be a dynamical realization of the topological Anderson insulator. We identify the conditions on the driving field necessary for observing such a transition. We realize such a disorder induced topological Floquet spectrum in the driven honeycomb lattice and quantum well models.

Finally, we show that two-dimensional periodically driven quantum systems with spatial disorder admit a unique topological phase, which we call the anomalous Floquet-Anderson insulator (AFAI). The AFAI is characterized by a quasienergy spectrum featuring chiral edge modes coexisting with a fully localized bulk. Such a spectrum is impossible for a time-independent, local Hamiltonian. These unique characteristics of the AFAI give rise to a new topologically protected nonequilibrium transport phenomenon: quantized, yet nonadiabatic, charge pumping. We identify the topological invariants that distinguish the AFAI from a trivial, fully localized phase, and show that the two phases are separated by a phase transition.

The thesis also present the study of disordered systems using Wegner's Flow equations. The Flow Equation Method was proposed as a technique for studying excited states in an interacting system in one dimension. We apply this method to a one-dimensional tight binding problem with power-law decaying hoppings. This model presents a transition as a function of the exponent of the decay. It is shown that the the entire phase diagram, i.e. the delocalized, critical and localized phases in these systems can be studied using this technique. Based on this technique, we develop a strong-bond renormalization group that procedure where we solve the Flow Equations iteratively. This renormalization group approach provides a new framework to study the transition in this system.