Photonics Active Filters Based on SiC Multi layer Structures: A Two Stage Active Circuit

Characteristics of tunable wavelength filters based on a-SiC:H multi-layered stacked cells are studied both theoretically and experimentally. Results show that the light-activated photonic device combines the demultiplexing operation with the simultaneous photodetection and self amplification of an optical signal. The sensor is a bias wavelength current-controlled device that make use of changes in the wavelength of the background to control the power delivered to the load, acting a photonic active filter. Its gain depends on the background wavelength that controls the electrical field profile across the device.

Power-and-area efficient 14-bit 1.5 MSample/s two-stage algorithmic ADC based on a mismatch-insensitive MDAC

IEEE International Symposium on Circuits and Systems, pp. 220 – 223, Seattle, EUA

Two stage abe fermentation with in situ pervaporation and high cell density

Dissertation presented to Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa for obtaining the master degree in Membrane Engineering

Going twice to the polls?: Optimality of two-stage voting procedures

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

Two-stage, extreme albitization of A-type granites from Rajasthan, NW India

Albitization is a common process during which hydrothermal fluids convert plagioclase and/or K-feldspar into nearly pure albite; however, its specific mechanism in granitoids is not well understood. The c. 1700 Ma A-type metaluminous ferroan granites in the Khetri complex of Rajasthan, NW India, have been albitized to a large extent by two metasomatic fronts, an initial transformation of oligoclase to nearly pure albite and a subsequent replacement of microcline by albite, with sharp contacts between the microcline-bearing and microcline-free zones. Albitization has bleached the original pinkish grey granite and turned it white. The mineralogical changes include transformation of oligoclase (similar to An(12)) and microcline (similar to Or(95)) to almost pure albite (similar to An(0 center dot 5-2)), amphibole from potassian ferropargasite (X-Fe 0 center dot 84-0 center dot 86) to potassic hastingsite (X-Fe 0 center dot 88-0 center dot 97) and actinolite (X-Fe 0 center dot 32-0 center dot 67), and biotite from annite (X-Fe 0 center dot 71-0 center dot 74) to annite (X-Fe 0 center dot 90-0 center dot 91). Whole-rock isocon diagrams show that, during albitization, the granites experienced major hydration, slight gain in Si and major gain in Na, whereas K, Mg, Fe and Ca were lost along with Rb, Ba, Sr, Zn, light rare earth elements and U. Whole-rock Sm-Nd isotope data plot on an apparent isochron of 1419 +/- 98 Ma and reveal significant disturbance and at least partial resetting of the intrusion age. Severe scatter in the whole-rock Rb-Sr isochron plot reflects the extreme Rb loss in the completely albitized samples, effectively freezing Sr-87/Sr-86 ratios in the albite granites at very high values (0 center dot 725-0 center dot 735). This indicates either infiltration of highly radiogenic Sr from the country rock or, more likely, radiogenic ingrowth during a considerable time lag (estimated to be at least 300 Myr) between original intrusion and albitization. The albitization took place at similar to 350-400 degrees C. It was caused by the infiltration of an ascending hydrothermal fluid that had acquired high Na/K and Na/Ca ratios during migration through metamorphic rocks at even lower temperatures in the periphery of the plutons. Oxygen isotope ratios increase from delta O-18 = 7 parts per thousand in the original granite to values of 9-10 parts per thousand in completely albitized samples, suggesting that the fluid had equilibrated with surrounding metamorphosed crust. A metasomatic model, using chromatographic theory of fluid infiltration, explains the process for generating the observed zonation in terms of a leading metasomatic front where oligoclase of the original granite is converted to albite, and a second, trailing front where microcline is also converted to albite. The temperature gradients driving the fluid infiltration may have been produced by the high heat production of the granites themselves. The confinement of the albitized granites along the NE-SW-trending Khetri lineament and the pervasive nature of the albitization suggest that the albitizing fluids possibly originated during reactivation of the lineament. More generally, steady-state temperature gradients induced by the high internal heat production of A-type granites may provide the driving force for similar metasomatic and ore-forming processes in other highly enriched granitoid bodies.

Eyes wide shut - unusual two stage repair of pectus excavatum and annuloaortic ectasia in a 37 year old marfan patient: Case report

We report about a 37 year old male patient with a pectus excavatum. The patient was in NYHA functional class III. After performed computed tomography the symptoms were thought to be related to the severity of chest deformation. A Ravitch-procedure had been accomplished in a district hospital in 2009. The crack of a metal bar led to a reevaluation 2010, in which surprisingly the presence of an annuloaortic ectasia (root 73 × 74 mm) in direct neighborhood of the formerly implanted metal-bars was diagnosed. Echocardiography revealed a severe aortic valve regurgitation, the left ventricle was massively dilated presenting a reduced ejection fraction of 45%. A marfan syndrome was suspected and the patient underwent a valve sparing aortic root replacement (David procedure) in our institution with an uneventful postoperative course. A review of the literature in combination with discussion of our case suggests the application of stronger recommendations towards preoperative cardiovascular assessment in patients with pectus excavatum.

Two-stage prograde and retrograde Variscan metamorphism of glaucophane-eclogites, blueschists and greenschists from Ile de Groix (Brittany, France)

On Ile de Groix, Variscan metamorphic former tholeiitic and alkaline basalts occur as glaucophane-eclogites, blueschists and greenschists in isolated lenses and layers within metapelites. Whole-rock delta O-18(SMOW) values of the metabasites show limited variations (10.4-12.0 parts per thousand) and no systematic differences among rock types and metamorphic grades. This provides no argument for large-scale blueschist-to-greenschist transformation driven by infiltration of externally derived fluids. Metamorphic mineralogical changes should have been triggered by internal fluids. Element variations in interlayered blue- and greenschists can be attributed to magmatic fractionation. Assemblages with garnet, clinopyroxene and glaucophane of a high-pressure/low-temperature (HP-LT) metamorphism M1, and NaCa-amphiboles (barroisite, magnesiohornblende, actinolite) of a medium-pressure/medium-temperature metamorphism M2 crystallized during deformation Dl. Detailed core-rim zonation profiles display increasing and then decreasing Al-IV in glaucophane of M1. NaCa-amphiboles of M2, mantling glaucophane and crystallized in porphyroblasts, show first increasing, then decreasing, Al-IV and Al-IV. Empirically calibrated thermobarometers allowed P-T path reconstructions. In glaucophane-eclogites of a metamorphic zone I, a prograde evolution to M1 peak conditions at 400-500 degreesC/10-12 kbar was followed by a retrograde P-T path within the glaucophane stability field. The subsequent M2 evolution was again prograde up to > 600 degreesC at 8 kbar and then retrograde. Similarly, in metamorphic zones II and III, prograde and retrograde paths of MI and M2 at lower maximal temperatures and pressures exist. The almost complete metamorphic cycle during M2 signalizes that the HP-LT rocks escaped from an early erosion by a moderate second burial event and explains the longlasting slow uplift with low average cooling rates.

Improving Portland Cement Concrete Mix Consistency and Production Rate through Two-Stage Mixing, TR-505, 2007

A two-stage mixing process for concrete involves mixing a slurry of cementitious materials and water, then adding the slurry to coarse and fine aggregate to form concrete. Some research has indicated that this process might facilitate dispersion of cementitious materials and improve cement hydration, the characteristics of the interfacial transition zone (ITZ) between aggregate and paste, and concrete homogeneity. The goal of the study was to find optimal mixing procedures for production of a homogeneous and workable mixture and quality concrete using a two-stage mixing operation. The specific objectives of the study are as follows: (1) To achieve optimal mixing energy and time for a homogeneous cementitious material, (2) To characterize the homogeneity and flow property of the pastes, (3) To investigate effective methods for coating aggregate particles with cement slurry, (4) To study the effect of the two-stage mixing procedure on concrete properties, (5) To obtain the improved production rates. Parameters measured for Phase I included: heat of hydration, maturity, and rheology tests were performed on the fresh paste samples, and compressive strength, degree of hydration, and scanning electron microscope (SEM) imaging tests were conducted on the cured specimens. For Phases II and III tests included slump and air content on fresh concrete and compressive and tensile strengths, rapid air void analysis, and rapid chloride permeability on hardened concrete.

Error models in hydrogeology applications

Notre consommation en eau souterraine, en particulier comme eau potable ou pour l'irrigation, a considérablement augmenté au cours des années. De nombreux problèmes font alors leur apparition, allant de la prospection de nouvelles ressources à la remédiation des aquifères pollués. Indépendamment du problème hydrogéologique considéré, le principal défi reste la caractérisation des propriétés du sous-sol. Une approche stochastique est alors nécessaire afin de représenter cette incertitude en considérant de multiples scénarios géologiques et en générant un grand nombre de réalisations géostatistiques. Nous rencontrons alors la principale limitation de ces approches qui est le coût de calcul dû à la simulation des processus d'écoulements complexes pour chacune de ces réalisations. Dans la première partie de la thèse, ce problème est investigué dans le contexte de propagation de l'incertitude, oú un ensemble de réalisations est identifié comme représentant les propriétés du sous-sol. Afin de propager cette incertitude à la quantité d'intérêt tout en limitant le coût de calcul, les méthodes actuelles font appel à des modèles d'écoulement approximés. Cela permet l'identification d'un sous-ensemble de réalisations représentant la variabilité de l'ensemble initial. Le modèle complexe d'écoulement est alors évalué uniquement pour ce sousensemble, et, sur la base de ces réponses complexes, l'inférence est faite. Notre objectif est d'améliorer la performance de cette approche en utilisant toute l'information à disposition. Pour cela, le sous-ensemble de réponses approximées et exactes est utilisé afin de construire un modèle d'erreur, qui sert ensuite à corriger le reste des réponses approximées et prédire la réponse du modèle complexe. Cette méthode permet de maximiser l'utilisation de l'information à disposition sans augmentation perceptible du temps de calcul. La propagation de l'incertitude est alors plus précise et plus robuste. La stratégie explorée dans le premier chapitre consiste à apprendre d'un sous-ensemble de réalisations la relation entre les modèles d'écoulement approximé et complexe. Dans la seconde partie de la thèse, cette méthodologie est formalisée mathématiquement en introduisant un modèle de régression entre les réponses fonctionnelles. Comme ce problème est mal posé, il est nécessaire d'en réduire la dimensionnalité. Dans cette optique, l'innovation du travail présenté provient de l'utilisation de l'analyse en composantes principales fonctionnelles (ACPF), qui non seulement effectue la réduction de dimensionnalités tout en maximisant l'information retenue, mais permet aussi de diagnostiquer la qualité du modèle d'erreur dans cet espace fonctionnel. La méthodologie proposée est appliquée à un problème de pollution par une phase liquide nonaqueuse et les résultats obtenus montrent que le modèle d'erreur permet une forte réduction du temps de calcul tout en estimant correctement l'incertitude. De plus, pour chaque réponse approximée, une prédiction de la réponse complexe est fournie par le modèle d'erreur. Le concept de modèle d'erreur fonctionnel est donc pertinent pour la propagation de l'incertitude, mais aussi pour les problèmes d'inférence bayésienne. Les méthodes de Monte Carlo par chaîne de Markov (MCMC) sont les algorithmes les plus communément utilisés afin de générer des réalisations géostatistiques en accord avec les observations. Cependant, ces méthodes souffrent d'un taux d'acceptation très bas pour les problèmes de grande dimensionnalité, résultant en un grand nombre de simulations d'écoulement gaspillées. Une approche en deux temps, le "MCMC en deux étapes", a été introduite afin d'éviter les simulations du modèle complexe inutiles par une évaluation préliminaire de la réalisation. Dans la troisième partie de la thèse, le modèle d'écoulement approximé couplé à un modèle d'erreur sert d'évaluation préliminaire pour le "MCMC en deux étapes". Nous démontrons une augmentation du taux d'acceptation par un facteur de 1.5 à 3 en comparaison avec une implémentation classique de MCMC. Une question reste sans réponse : comment choisir la taille de l'ensemble d'entrainement et comment identifier les réalisations permettant d'optimiser la construction du modèle d'erreur. Cela requiert une stratégie itérative afin que, à chaque nouvelle simulation d'écoulement, le modèle d'erreur soit amélioré en incorporant les nouvelles informations. Ceci est développé dans la quatrième partie de la thèse, oú cette méthodologie est appliquée à un problème d'intrusion saline dans un aquifère côtier. -- Our consumption of groundwater, in particular as drinking water and for irrigation, has considerably increased over the years and groundwater is becoming an increasingly scarce and endangered resource. Nofadays, we are facing many problems ranging from water prospection to sustainable management and remediation of polluted aquifers. Independently of the hydrogeological problem, the main challenge remains dealing with the incomplete knofledge of the underground properties. Stochastic approaches have been developed to represent this uncertainty by considering multiple geological scenarios and generating a large number of realizations. The main limitation of this approach is the computational cost associated with performing complex of simulations in each realization. In the first part of the thesis, we explore this issue in the context of uncertainty propagation, where an ensemble of geostatistical realizations is identified as representative of the subsurface uncertainty. To propagate this lack of knofledge to the quantity of interest (e.g., the concentration of pollutant in extracted water), it is necessary to evaluate the of response of each realization. Due to computational constraints, state-of-the-art methods make use of approximate of simulation, to identify a subset of realizations that represents the variability of the ensemble. The complex and computationally heavy of model is then run for this subset based on which inference is made. Our objective is to increase the performance of this approach by using all of the available information and not solely the subset of exact responses. Two error models are proposed to correct the approximate responses follofing a machine learning approach. For the subset identified by a classical approach (here the distance kernel method) both the approximate and the exact responses are knofn. This information is used to construct an error model and correct the ensemble of approximate responses to predict the "expected" responses of the exact model. The proposed methodology makes use of all the available information without perceptible additional computational costs and leads to an increase in accuracy and robustness of the uncertainty propagation. The strategy explored in the first chapter consists in learning from a subset of realizations the relationship between proxy and exact curves. In the second part of this thesis, the strategy is formalized in a rigorous mathematical framework by defining a regression model between functions. As this problem is ill-posed, it is necessary to reduce its dimensionality. The novelty of the work comes from the use of functional principal component analysis (FPCA), which not only performs the dimensionality reduction while maximizing the retained information, but also allofs a diagnostic of the quality of the error model in the functional space. The proposed methodology is applied to a pollution problem by a non-aqueous phase-liquid. The error model allofs a strong reduction of the computational cost while providing a good estimate of the uncertainty. The individual correction of the proxy response by the error model leads to an excellent prediction of the exact response, opening the door to many applications. The concept of functional error model is useful not only in the context of uncertainty propagation, but also, and maybe even more so, to perform Bayesian inference. Monte Carlo Markov Chain (MCMC) algorithms are the most common choice to ensure that the generated realizations are sampled in accordance with the observations. Hofever, this approach suffers from lof acceptance rate in high dimensional problems, resulting in a large number of wasted of simulations. This led to the introduction of two-stage MCMC, where the computational cost is decreased by avoiding unnecessary simulation of the exact of thanks to a preliminary evaluation of the proposal. In the third part of the thesis, a proxy is coupled to an error model to provide an approximate response for the two-stage MCMC set-up. We demonstrate an increase in acceptance rate by a factor three with respect to one-stage MCMC results. An open question remains: hof do we choose the size of the learning set and identify the realizations to optimize the construction of the error model. This requires devising an iterative strategy to construct the error model, such that, as new of simulations are performed, the error model is iteratively improved by incorporating the new information. This is discussed in the fourth part of the thesis, in which we apply this methodology to a problem of saline intrusion in a coastal aquifer.

Prosthetic joint infections : A retrospective study on the timing of reimplantation in a two-stage exchange

Different therapeutic options for prosthetic joint infections exist, but surgery remains the key. With a two-stage exchange procedure, a success rate above 90% can be expected. Currently, there is no consensus regarding the optimal duration between explantation and the reimplantation in a two-stage procedure. The aim of this study was to retrospectively compare treatment outcomes between short-interval and long-interval two-stage exchanges. Patients having a two-stage exchange of a hip or knee prosthetic joint infection at Lausanne University Hospital (Switzerland) between 1999 and 2013 were included. The satisfaction of the patient, the function of the articulation and the eradication of infection, were compared between patients having a short (2 to 4 weeks) versus a long (4 weeks and more) interval during a two-stage procedure. Patient satisfaction was defined as good if the patient did not have pain and bad if the patient had pain. Functional outcome was defined good if the patient had a prosthesis in place and could walk, medium if the prosthesis was in place but the patient could not walk, and bad if the prosthesis was no longer in place. Infection outcome was considered good if there had been no re-infection and bad if there had been a re-infection of the prosthesis 145 patients (100 hips, 45 knees) were identified with a median age of 68 years (range 19-103). The median hospital stay was 58 days (range 10-402). The median follow-up was 12.9 months (range 0.5-152). 28 % and 72 % of the patients had a short-interval and long-interval exchange of the prosthesis, respectively. Patient satisfaction, functional outcome and infection outcome for patients having a short versus a long interval are reported in the Table. The patient satisfaction was higher when a long interval was performed whereas the functional and infection outcomes were higher when a short interval was performed. According to this study a short-interval exchange appears preferable to a long interval, especially in the view of treatment effectiveness and functional outcome.

A simple model of two-stage choice

I provide choice-theoretic foundations for a simple two-stage model, called transitive shortlist methods, where choices are made by sequentially by applying a pair of transitive preferences (or rationales) to eliminate inferior alternatives. Despite its simplicity, the model accommodates a wide range of choice phenomena including the status quo bias, framing, homophily, compromise, and limited willpower. I establish that the model can be succinctly characterized in terms of some well-documented context effects in choice. I also show that the underlying rationales are straightforward to determine from readily observable reversals in choice. Finally, I highlight the usefulness of these results in a variety of applications.

Optimization of Two Stage Process for the Growth of In2S3 , CuInSe2 and CuIn (Sel-xSx)2Thin Films for Solar Cell Application

Two stage processes consisting of precursor preparation by thermal evaporation followed by chalcogenisation in the required atmosphere is found to be a feasible technique for the PV materials such as n-Beta In2S3, p-CulnSe2, p-CulnS2 and p-CuIn(Sel_xSx)2. The growth parameters such as chalcogenisation temperature and duration of chalcogenisation etc have been optimised in the present study.Single phase Beta-In2S3 thin films can be obtained by sulfurising the indium films above 300°C for 45 minutes. Low sulfurisation temperatures required prolonged annealing after the sulfurisation to obtain single phase Beta-1n2S3, which resulted in high material loss. The maximum band gap of 2.58 eV was obtained for the nearly stoichiometric Beta-In2S3 film which was sulfurised at 350°C. This wider band gap, n type Beta-In2S3 can be used as an alternative to toxic CdS as window layer in photovoltaics .The systematic study on the structural optical and electrical properties of CuInSe2 films by varying the process parameters such as the duration of selenization and the selenization temperature led to the conclusion that for the growth of single-phase CuInSe2, the optimum selenization temperature is 350°C and duration is 3 hours. The presence of some binary phases in films for shorter selenization period and lower selenization temperature may be due to the incomplete reaction and indium loss. Optical band gap energy of 1.05 eV obtained for the films under the optimum condition.In order to obtain a closer match to the solar spectrum it is desirable to increase the band gap of the CulnSe2 by a few meV . Further research works were carried out to produce graded band gap CuIn(Se,S)2 absorber films by incorporation of sulfur into CuInSe2. It was observed that when the CulnSe2 prepared by two stage process were post annealed in sulfur atmosphere, the sulfur may be occupying the interstitial positions or forming a CuInS2 phase along with CuInSe2 phase. The sulfur treatment during the selenization process OfCu11 ln9 precursors resulted in Culn (Se,S)2 thin films. A band gap of 1.38 eV was obtained for the CuIn(Se,S)2.The optimised thin films n-beta 1n2S3, p-CulnSe2 and p-Culn(Sel-xSx)2 can be used for fabrication of polycrystalline solar cells.

Technical and scale efficiency of cassava production system in Delta State, Nigeria: an application of Two-Stage DEA approach

The present study examines the level of pure technical and scale efficiencies of cassava production system including its sub-processes (that is production and processing stages) of 278 cassava farmers/processors from three regions of Delta State, Nigeria by applying Two-Stage Data Envelopment Analysis (DEA) approach. Results reveal that pure technical efficiency (PTE) is significantly lower at the production stage 0.41 vs 0.55 for the processing stage, but scale efficiency (SE) is high at both stages (0.84 and 0.87), implying that productivity can be improved substantially by reallocation of resources and adjusting operation size. The socio-economic determinants exert differential impacts on PTE and SE at each stage. Overall, education, experience and main occupation as farmer significantly improve SE while subsistence pressure reduces it. Extension contact significantly improves SE at the processing stage but reduces PTE and SE overall. Inverse size-PTE and size-SE relationships exist in cassava production system. In other words, large/medium farms are technically and scale inefficient. Gender gap exists in performance. Male farmers are technically efficient at processing stage but scale inefficient overall. Farmers in northern region are technically efficient. Investments in education, extension services and infrastructure are suggested as policy options to improve the cassava sector in Nigeria.