New features of the layer-by-layer deposition of microcrystalline silicon films revealed by spectroscopic ellipsometry and high resolution transmission electron microscopy

Spectroscopic ellipsometry and high resolution transmission electron microscopy have been used to characterize microcrystalline silicon films. We obtain an excellent agreement between the multilayer model used in the analysis of the optical data and the microscopy measurements. Moreover, thanks to the high resolution achieved in the microscopy measurements and to the improved optical models, two new features of the layer-by-layer deposition of microcrystalline silicon have been detected: i) the microcrystalline films present large crystals extending from the a-Si:H substrate to the film surface, despite the sequential process in the layer-by-layer deposition; and ii) a porous layer exists between the amorphous silicon substrate and the microcrystalline silicon film.

Assessing the use of very high resolution data to predict species distribution in a mountain environment

Nowadays, Species Distribution Models (SDMs) are a widely used tool. Using different statistical approaches these models reconstruct the realized niche of a species using presence data and a set of variables, often topoclimatic. There utilization range is quite large from understanding single species requirements, to the creation of nature reserve based on species hotspots, or modeling of climate change impact, etc... Most of the time these models are using variables at a resolution of 50km x 50km or 1 km x 1 km. However in some cases these models are used with resolutions below the kilometer scale and thus called high resolution models (100 m x 100 m or 25 m x 25 m). Quite recently a new kind of data has emerged enabling precision up to lm x lm and thus allowing very high resolution modeling. However these new variables are very costly and need an important amount of time to be processed. This is especially the case when these variables are used in complex calculation like models projections over large areas. Moreover the importance of very high resolution data in SDMs has not been assessed yet and is not well understood. Some basic knowledge on what drive species presence-absences is still missing. Indeed, it is not clear whether in mountain areas like the Alps coarse topoclimatic gradients are driving species distributions or if fine scale temperature or topography are more important or if their importance can be neglected when balance to competition or stochasticity. In this thesis I investigated the importance of very high resolution data (2-5m) in species distribution models using either very high resolution topographic, climatic or edaphic variables over a 2000m elevation gradient in the Western Swiss Alps. I also investigated more local responses of these variables for a subset of species living in this area at two precise elvation belts. During this thesis I showed that high resolution data necessitates very good datasets (species and variables for the models) to produce satisfactory results. Indeed, in mountain areas, temperature is the most important factor driving species distribution and needs to be modeled at very fine resolution instead of being interpolated over large surface to produce satisfactory results. Despite the instinctive idea that topographic should be very important at high resolution, results are mitigated. However looking at the importance of variables over a large gradient buffers the importance of the variables. Indeed topographic factors have been shown to be highly important at the subalpine level but their importance decrease at lower elevations. Wether at the mountane level edaphic and land use factors are more important high resolution topographic data is more imporatant at the subalpine level. Finally the biggest improvement in the models happens when edaphic variables are added. Indeed, adding soil variables is of high importance and variables like pH are overpassing the usual topographic variables in SDMs in term of importance in the models. To conclude high resolution is very important in modeling but necessitate very good datasets. Only increasing the resolution of the usual topoclimatic predictors is not sufficient and the use of edaphic predictors has been highlighted as fundamental to produce significantly better models. This is of primary importance, especially if these models are used to reconstruct communities or as basis for biodiversity assessments. -- Ces dernières années, l'utilisation des modèles de distribution d'espèces (SDMs) a continuellement augmenté. Ces modèles utilisent différents outils statistiques afin de reconstruire la niche réalisée d'une espèce à l'aide de variables, notamment climatiques ou topographiques, et de données de présence récoltées sur le terrain. Leur utilisation couvre de nombreux domaines allant de l'étude de l'écologie d'une espèce à la reconstruction de communautés ou à l'impact du réchauffement climatique. La plupart du temps, ces modèles utilisent des occur-rences issues des bases de données mondiales à une résolution plutôt large (1 km ou même 50 km). Certaines bases de données permettent cependant de travailler à haute résolution, par conséquent de descendre en dessous de l'échelle du kilomètre et de travailler avec des résolutions de 100 m x 100 m ou de 25 m x 25 m. Récemment, une nouvelle génération de données à très haute résolution est apparue et permet de travailler à l'échelle du mètre. Les variables qui peuvent être générées sur la base de ces nouvelles données sont cependant très coûteuses et nécessitent un temps conséquent quant à leur traitement. En effet, tout calcul statistique complexe, comme des projections de distribution d'espèces sur de larges surfaces, demande des calculateurs puissants et beaucoup de temps. De plus, les facteurs régissant la distribution des espèces à fine échelle sont encore mal connus et l'importance de variables à haute résolution comme la microtopographie ou la température dans les modèles n'est pas certaine. D'autres facteurs comme la compétition ou la stochasticité naturelle pourraient avoir une influence toute aussi forte. C'est dans ce contexte que se situe mon travail de thèse. J'ai cherché à comprendre l'importance de la haute résolution dans les modèles de distribution d'espèces, que ce soit pour la température, la microtopographie ou les variables édaphiques le long d'un important gradient d'altitude dans les Préalpes vaudoises. J'ai également cherché à comprendre l'impact local de certaines variables potentiellement négligées en raison d'effets confondants le long du gradient altitudinal. Durant cette thèse, j'ai pu monter que les variables à haute résolution, qu'elles soient liées à la température ou à la microtopographie, ne permettent qu'une amélioration substantielle des modèles. Afin de distinguer une amélioration conséquente, il est nécessaire de travailler avec des jeux de données plus importants, tant au niveau des espèces que des variables utilisées. Par exemple, les couches climatiques habituellement interpolées doivent être remplacées par des couches de température modélisées à haute résolution sur la base de données de terrain. Le fait de travailler le long d'un gradient de température de 2000m rend naturellement la température très importante au niveau des modèles. L'importance de la microtopographie est négligeable par rapport à la topographie à une résolution de 25m. Cependant, lorsque l'on regarde à une échelle plus locale, la haute résolution est une variable extrêmement importante dans le milieu subalpin. À l'étage montagnard par contre, les variables liées aux sols et à l'utilisation du sol sont très importantes. Finalement, les modèles de distribution d'espèces ont été particulièrement améliorés par l'addition de variables édaphiques, principalement le pH, dont l'importance supplante ou égale les variables topographique lors de leur ajout aux modèles de distribution d'espèces habituels.

Very high-resolution digital elevation models: are multi-scale-derived variables ecologically relevant?

1. Digital elevation models (DEMs) are often used in landscape ecology to retrieve elevation or first derivative terrain attributes such as slope or aspect in the context of species distribution modelling. However, DEM-derived variables are scale-dependent and, given the increasing availability of very high-resolution (VHR) DEMs, their ecological relevancemust be assessed for different spatial resolutions. 2. In a study area located in the Swiss Western Alps, we computed VHR DEMs-derived variables related to morphometry, hydrology and solar radiation. Based on an original spatial resolution of 0.5 m, we generated DEM-derived variables at 1, 2 and 4 mspatial resolutions, applying a Gaussian Pyramid. Their associations with local climatic factors, measured by sensors (direct and ambient air temperature, air humidity and soil moisture) as well as ecological indicators derived fromspecies composition, were assessed with multivariate generalized linearmodels (GLM) andmixed models (GLMM). 3. Specific VHR DEM-derived variables showed significant associations with climatic factors. In addition to slope, aspect and curvature, the underused wetness and ruggedness indices modelledmeasured ambient humidity and soilmoisture, respectively. Remarkably, spatial resolution of VHR DEM-derived variables had a significant influence on models' strength, with coefficients of determination decreasing with coarser resolutions or showing a local optimumwith a 2 mresolution, depending on the variable considered. 4. These results support the relevance of using multi-scale DEM variables to provide surrogates for important climatic variables such as humidity, moisture and temperature, offering suitable alternatives to direct measurements for evolutionary ecology studies at a local scale.

Predicting richness and composition in mountain insect communities at high resolution: a new test of the SESAM framework

Aim The aim of this study was to test different modelling approaches, including a new framework, for predicting the spatial distribution of richness and composition of two insect groups. Location The western Swiss Alps. Methods We compared two community modelling approaches: the classical method of stacking binary prediction obtained fromindividual species distribution models (binary stacked species distribution models, bS-SDMs), and various implementations of a recent framework (spatially explicit species assemblage modelling, SESAM) based on four steps that integrate the different drivers of the assembly process in a unique modelling procedure. We used: (1) five methods to create bS-SDM predictions; (2) two approaches for predicting species richness, by summing individual SDM probabilities or by modelling the number of species (i.e. richness) directly; and (3) five different biotic rules based either on ranking probabilities from SDMs or on community co-occurrence patterns. Combining these various options resulted in 47 implementations for each taxon. Results Species richness of the two taxonomic groups was predicted with good accuracy overall, and in most cases bS-SDM did not produce a biased prediction exceeding the actual number of species in each unit. In the prediction of community composition bS-SDM often also yielded the best evaluation score. In the case of poor performance of bS-SDM (i.e. when bS-SDM overestimated the prediction of richness) the SESAM framework improved predictions of species composition. Main conclusions Our results differed from previous findings using community-level models. First, we show that overprediction of richness by bS-SDM is not a general rule, thus highlighting the relevance of producing good individual SDMs to capture the ecological filters that are important for the assembly process. Second, we confirm the potential of SESAM when richness is overpredicted by bS-SDM; limiting the number of species for each unit and applying biotic rules (here using the ranking of SDM probabilities) can improve predictions of species composition

Can chest high-resolution computed tomography findings diagnose pulmonary alveolar microlithiasis?

AbstractObjective:The present study was aimed at retrospectively reviewing high-resolution computed tomography (HRCT) findings in patients with pulmonary alveolar microlithiasis in order to evaluate the frequency of tomographic findings and their distribution in the lung parenchyma.Materials and Methods:Thirteen patients (9 females and 4 males; age, 9 to 59 years; mean age, 34.5 years) were included in the present study. The HRCT images were independently evaluated by two observers whose decisions were made by consensus. The inclusion criterion was the presence of abnormalities typical of pulmonary alveolar microlithiasis at HRCT, which precludes lung biopsy. However, in 6 cases lung biopsy was performed.Results:Ground-glass opacities and small parenchymal nodules were the predominant tomographic findings, present in 100% of cases, followed by small subpleural nodules (92.3%), subpleural cysts (84.6%), subpleural linear calcifications (69.2%), crazy-paving pattern (69.2%), fissure nodularity (53.8%), calcification along interlobular septa (46.2%) and dense consolidation (46.2%).Conclusion:As regards distribution of the lesions, there was preferential involvement of the lower third of the lungs. No predominance of distribution in axial and anteroposterior directions was observed.

High-resolution computed tomography and histopathological findings in hypersensitivity pneumonitis: a pictorial essay

Abstract Hypersensitivity pneumonitis is a diffuse interstitial and granulomatous lung disease caused by the inhalation of any one of a number of antigens. The objective of this study was to illustrate the spectrum of abnormalities in high-resolution computed tomography and histopathological findings related to hypersensitivity pneumonitis. We retrospectively evaluated patients who had been diagnosed with hypersensitivity pneumonitis (on the basis of clinical-radiological or clinical-radiological-pathological correlations) and had undergone lung biopsy. Hypersensitivity pneumonitis is clinically divided into acute, subacute, and chronic forms; high-resolution computed tomography findings correlate with the time of exposure; and the two occasionally overlap. In the subacute form, centrilobular micronodules, ground-glass opacities, and air trapping are characteristic high-resolution computed tomography findings, whereas histopathology shows lymphocytic inflammatory infiltrates, bronchiolitis, variable degrees of organizing pneumonia, and giant cells. In the chronic form, high-resolution computed tomography shows traction bronchiectasis, honeycombing, and lung fibrosis, the last also being seen in the biopsy sample. A definitive diagnosis of hypersensitivity pneumonitis can be made only through a multidisciplinary approach, by correlating clinical findings, exposure history, high-resolution computed tomography findings, and lung biopsy findings.

High-Resolution Magnetic Resonance Imaging Can Reliably Detect Orbital Tumor Recurrence after Enucleation in Children with Retinoblastoma.

PURPOSE: Orbital tumor recurrence is a rare but serious complication in children with retinoblastoma, leading to a high risk of metastasis and death. Therefore, we assume that these recurrences have to be detected and treated as early as possible. Preliminary studies used magnetic resonance imaging (MRI) to evaluate postsurgical findings in the orbit. In this study, we assessed the diagnostic accuracy of high-resolution MRI to detect orbital tumor recurrence in children with retinoblastoma in a large study cohort. DESIGN: Consecutive retrospective study (2007-2013) assessing MRI findings after enucleation. PARTICIPANTS: A total of 103 MRI examinations of 55 orbits (50 children, 27 male/23 female, mean age 16.3±12.4 months) with a median time of 8 months (range, 0-93) after enucleation for retinoblastoma. METHODS: High-resolution MRI using orbital surface coils was performed on 1.5 Tesla MRI systems to assess abnormal orbital findings. MAIN OUTCOME MEASURES: Five European experts in retinoblastoma imaging evaluated the MRI examinations regarding the presence of abnormal orbital gadolinium enhancement and judged them as "definitive tumor," "suspicious of tumor," "postsurgical condition/scar formation," or "without pathologic findings." The findings were correlated to histopathology (if available), MRI, and clinical follow-up. RESULTS: Abnormal orbital enhancement was a common finding after enucleation (100% in the first 3 months after enucleation, 64.3% >3 years after enucleation). All histopathologically confirmed tumor recurrences (3 of 55 orbits, 5.5%) were correctly judged as "definitive tumor" in MRI. Two orbits from 2 children rated as "suspicious of tumor" received intravenous chemotherapy without histopathologic confirmation; further follow-up (67 and 47 months) revealed no sign of tumor recurrence. In 90.2%, no tumor was suspected on MRI, which was clinically confirmed during follow-up (median follow-up after enucleation, 45 months; range, 8-126). CONCLUSIONS: High-resolution MRI with orbital surface coils may reliably distinguish between common postsurgical contrast enhancement and orbital tumor recurrence, and therefore may be a useful tool to evaluate orbital tumor recurrence after enucleation in children with retinoblastoma. We recommend high-resolution MRI as a potential screening tool for the orbit in children with retinoblastoma to exclude tumor recurrence, especially in high-risk patients within the critical first 2 years after enucleation.

Perfil químico de cultivares de feijão (phaseolus vulgaris) pela técnica de high resolution magic angle spinning (HR-MAS)

The application of one-dimensional proton high-resolution magic angle spinning (¹H HR-MAS) NMR combined with a typical advantages of solid and liquid-state NMR techniques was used as input variables for the multivariate statistical analysis. In this paper, different cultivars of beans (Phaseolus vulgaris) developed and in development by Embrapa - Arroz e Feijão were analyzed by ¹H HR-MAS, which have been demonstrated to be a valuable tool in its differentiation according chemical composition and avoid the manipulation of the samples as used in other techniques.

Determination of levodopa in human plasma by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS): application to a bioequivalence study

A sensitive, accurate and simple method using HPLC-MS/MS was developed and validated for levodopa quantitation in human plasma. Analysis was achieved on a pursuit® C18 analytical column (5 µm; 150 x 4.6 mm i.d.) using a mobile phase (methanol and water , 90:10, v/v) containing formic acid 0.5% v/v, after extracting the samples using a simple protein plasma precipitation with perchloric acid. The developed method was validated in accordance with ANVISA guidelines and was successfully applied to a bioequivalence study in 60 healthy volunteers demonstrating the feasibility and reliability of the proposed method.

A clinical gamma camera-based pinhole collimated system for high resolution small animal SPECT imaging

The main objective of the present study was to upgrade a clinical gamma camera to obtain high resolution tomographic images of small animal organs. The system is based on a clinical gamma camera to which we have adapted a special-purpose pinhole collimator and a device for positioning and rotating the target based on a computer-controlled step motor. We developed a software tool to reconstruct the target’s three-dimensional distribution of emission from a set of planar projections, based on the maximum likelihood algorithm. We present details on the hardware and software implementation. We imaged phantoms and heart and kidneys of rats. When using pinhole collimators, the spatial resolution and sensitivity of the imaging system depend on parameters such as the detector-to-collimator and detector-to-target distances and pinhole diameter. In this study, we reached an object voxel size of 0.6 mm and spatial resolution better than 2.4 and 1.7 mm full width at half maximum when 1.5- and 1.0-mm diameter pinholes were used, respectively. Appropriate sensitivity to study the target of interest was attained in both cases. Additionally, we show that as few as 12 projections are sufficient to attain good quality reconstructions, a result that implies a significant reduction of acquisition time and opens the possibility for radiotracer dynamic studies. In conclusion, a high resolution single photon emission computed tomography (SPECT) system was developed using a commercial clinical gamma camera, allowing the acquisition of detailed volumetric images of small animal organs. This type of system has important implications for research areas such as Cardiology, Neurology or Oncology.

Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis

High resolution proton nuclear magnetic resonance spectroscopy (¹H MRS) can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA) was used to classify 11.7 T ¹H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis) and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out cross-validation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.

Striatal and extrastriatal dopamine D2/3 receptors studied with [11C]raclopride and high-resolution PET

The human striatum is a heterogeneous structure representing a major part of the dopamine (DA) system’s basal ganglia input and output. Positron emission tomography (PET) is a powerful tool for imaging DA neurotransmission. However, PET measurements suffer from bias caused by the low spatial resolution, especially when imaging small, D2/3 -rich structures such as the ventral striatum (VST). The brain dedicated high-resolution PET scanner, ECAT HRRT (Siemens Medical Solutions, Knoxville, TN, USA) has superior resolution capabilities than its predecessors. In the quantification of striatal D2/3 binding, the in vivo highly selective D2/3 antagonist [11C] raclopride is recognized as a well-validated tracer. The aim of this thesis was to use a traditional test-retest setting to evaluate the feasibility of utilizing the HRRT scanner for exploring not only small brain regions such as the VST but also low density D2/3 areas such as cortex. It was demonstrated that the measurement of striatal D2/3 binding was very reliable, even when studying small brain structures or prolonging the scanning interval. Furthermore, the cortical test-retest parameters displayed good to moderate reproducibility. For the first time in vivo, it was revealed that there are significant divergent rostrocaudal gradients of [11C]raclopride binding in striatal subregions. These results indicate that high-resolution [11C]raclopride PET is very reliable and its improved sensitivity means that it should be possible to detect the often very subtle changes occurring in DA transmission. Another major advantage is the possibility to measure simultaneously striatal and cortical areas. The divergent gradients of D2/3 binding may have functional significance and the average distribution binding could serve as the basis for a future database. Key words: dopamine, PET, HRRT, [11C]raclopride, striatum, VST, gradients, test-retest.