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Estimation of the total column water vapor (CWV) content of the atmosphere plays an important role in the atmospheric compensation (AC) of remotely sensed hyperspectral images collected in the visible and near infrared (VNIR) spectral range. Most of the proposed CWV retrieval methods provide accurate estimates as long as other significant atmospheric parameters are known. Those parameters are not generally available and must in turn be estimated. In this article, a new approach based on deep learning is proposed that allows the estimation of CWV without the knowledge of the atmospheric visibility, the solar zenith angle, and the atmospheric point spread function (PSF). The proposed approach includes a training strategy based on synthetic data that are generated according to an accurate radiative-transfer model, and by exploiting reflectance spectral libraries and the MODTRAN radiative-transfer code. Experiments on simulated data are carried out to analyze the performance of the proposed deep neural network with reference to both aerial and satellite applications. Furthermore, an example of the results provided by the network in a real application is shown. For this purpose, the network is applied to data acquired by an airborne hyperspectral sensor operating in the VNIR spectral range. [ABSTRACT FROM AUTHOR]

This paper deals with atmospheric correction in hyperspectral data acquired in the long-wave infrared (LWIR) spectral range. Atmospheric compensation (AC) is approached from a new perspective in that it is reformulated as an estimation problem on a low-rank subspace. Specifically, a subspace-based model is exploited to represent both the atmospheric transmittance and the upwelling radiance. Taking into account the inherent correlation between these two quantities, we adopt a subspace model that constrains them to vary in a physically consistent way. Exploiting such a model, AC is formulated as a nonlinear least-squares estimation problem. An automatic procedure is proposed to estimate the unknown parameters, which is based only on the image analysis and does not need any atmospheric measurements. Results of an extensive experimental analysis carried out on simulated data are used to discuss the performance of the algorithm with respect to different atmospheric conditions. Finally, experimental evidence over a real LWIR hyperspectral image is provided. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the temperature and emissivity separation (TES) problem from hyperspectral data acquired in the long-wave infrared region (LWIR) of the electromagnetic spectrum. We derive a general class of TES algorithms [subspace-based TES (SBTES)] relying on the assumption that the emissivity spectra of natural and man-made materials can be well represented in a given subspace of the original data space. Specifically, by exploiting the subspace representation and the Gaussian model for the noise affecting LWIR hyperspectral data, we approach TES under a statistical perspective by obtaining the maximum likelihood estimates of both the temperature and the spectral emissivity. The proposed approach originates several algorithms whose specific form depends on the particular basis matrix adopted to address the emissivity subspace. We study the performance of the presented class of algorithms and derive theoretical bounds on the accuracy of the temperature and emissivity estimators. Furthermore, by specifying two basis matrices for the emissivity subspace, we propose two different algorithms within the SBTES class. Finally, we present the results of an extensive experimental analysis carried out over simulated data to assess and compare the performance of the two presented algorithms. [ABSTRACT FROM AUTHOR]

Investigates the epitaxial molecular beam epitaxy growth of nanometric germanium layers on silicon (001) 2 X 1. Characterization methods used to control the growth of available germanium molecular beam epitaxy deposits; Details on the experiment; Results of the study.

The knowledge of atmospheric column water vapor concentration is crucial for compensating water absorption effects in remote sensing data. Several algorithms for the estimation of such a parameter were proposed in the past. One of the most effective algorithms is the atmospheric precorrected differential absorption (APDA) technique. APDA relies on a simplified radiative transfer model (RTM) that does not account for the spatial variability of the adjacency effects. In this paper, we study the impact of the simplified RTM assumption on the performance of the algorithm by exploiting a more realistic and well-established RTM. Starting from such a model, we derive a new water retrieval algorithm called low-rank subspace projection-based water estimator. It exploits the high degree of spectral correlation experienced in the reflectances of most of the existing materials. An extensive experimental analysis is carried out on simulated data in order to assess and compare the performance of the two algorithms. Simulation results allow the critical analysis of the two algorithms by highlighting their strengths and drawbacks. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the constant false-alarm rate (CFAR) property of the RX anomaly detector which is widely used for the analysis of hyperspectral data. The RX detector relies on an adaptive scheme where the mean vector and the covariance matrix of the background are locally estimated from the image pixels themselves. First, demeaning is accomplished by removing the estimated local background mean value, and then, the covariance matrix is estimated in a homogeneous neighborhood of each pixel. In principle, if the local mean is perfectly removed and the covariance matrix is estimated from background pixels sharing the same covariance matrix, the RX algorithm has the CFAR property, which is highly desirable in practical applications. The CFAR behavior of the algorithm also requires the spatial stationarity of the random noise affecting the hyperspectral image. In data collected by new-generation sensors, such an assumption is not valid because photon noise contribution, which depends on the spatially varying signal level, is not negligible. This has motivated us to analyze the behavior of the RX algorithm with respect to the CFAR property in data affected by signal-dependent (SD) noise. In this paper, we show both theoretically and experimentally that the SD noise is one of the causes of the non-CFAR behavior of the RX detector that we have experienced in many practical situations. We propose a strategy to enhance the robustness of the anomaly detection scheme with respect to the CFAR property based on an adaptive nonlinear transform aimed at reducing the dependence of the noise on the signal level. Experiments on simulated data and real data collected by a new hyperspectral camera are also presented and discussed. [ABSTRACT FROM AUTHOR]

Orthogonal subspace projection (OSP) is a powerful tool for dimensionality reduction (DR) in hyperspectral images (HSIs). In the OSP approach, the basis of the signal subspace must be estimated from the data themselves. Such estimation task is referred to as signal subspace identification (SSI). Most of the SSI methods in the literature are based on the analysis of the data second-order statistics (SOS) and have two main drawbacks: 1) They do not take into account the rare signal components (or rare vectors), 2) they assume that noise is spatially stationary. Rare vectors are those signal components that are present in pixels scarcely represented in the image and linearly independent on the signal components characterizing the rest of the image pixels. SOS-based SSI algorithms estimate the signal subspace addressing mostly the background and ignoring the presence of the rare pixels. This may be detrimental for the performance of detection algorithms when DR is adopted as a pre-processing step in small target detection applications. In this paper, a new technique for SSI in HSIs is presented. The algorithm is developed to account for both the abundant and the rare signal components. The method is derived by assuming a signal-dependent model for the noise affecting the data. This makes the SSI algorithm particularly suitable for the processing of images acquired by new generation sensors where, due to the improved sensitivity of the electronic components, noise includes a signal-dependent term. Results on simulated data are discussed, and the comparison with a recently proposed technique based on the analysis of SOS is performed. Furthermore, the results obtained by applying the SSI algorithm to a real HSI affected by signal-dependent noise are presented and discussed. [ABSTRACT FROM AUTHOR]

In this paper, a new algorithm for striping noise reduction in hyperspectral images is proposed. The new algorithm exploits the orthogonal subspace approach to estimate the striping component and to remove it from the image, preserving the useful signal. The algorithm does not introduce artifacts in the data and also takes into account the dependence on the signal intensity of the striping component. The effectiveness of the algorithm in reducing striping noise is experimentally demonstrated on real data acquired both by airborne and satellite hyperspectral sensors. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of signal subspace estimation for dimensionality reduction (DR) in hyperspectral images in the presence of rare pixels, i.e., pixels that are scarcely represented in the image and containing spectral components that are linearly independent of the background. Most of the classical methods proposed in the literature are based on the analysis second-order statistics (SOS), which are weakly influenced by the rare signals. Therefore, such techniques estimate the signal subspace addressing mostly the background and ignoring the presence of rare pixels. This may reduce the target/background spectral contrast, thus decreasing the detection performance when DR is adopted as preprocessing task in small-target detection applications. In this paper, a new robust algorithm, namely, robust signal subspace estimation (RSSE), is developed, which preserves both abundant and rare signal components. It combines the analysis of SOS and a recent approach based on the analysis of the l2∞ norm. The novel contribution of this paper is twofold. First, the RSSE algorithm is presented, which includes a new iterative procedure to derive the signal subspace and an original statistical method to estimate the data dimensionality. Second, an ad simulation strategy is proposed to assess the performance of signal subspace estimation methods in the presence of rare signal components. The procedure is adopted to compare the RSSE algorithm with a classical technique based on the analysis of SOS. The results obtained by applying the two methods on a real Airborne Visible Infrared Imaging Spectrometer hyperspectral image also presented and discussed. [ABSTRACT FROM AUTHOR]

A new algorithm is presented for the detection of airborne targets by means of infrared sensors operating in naval surveillance scenarios. The proposed algorithm consists of two steps: background clutter removal and detection over the residual clutter. The algorithm is fully automatic and its implementation does not require the tuning of any parameter other than the threshold for setting the probability of false alarm. The algorithm performance is investigated by means of a sequence of experimental IR images taken in a typical maritime environment. The results show that the proposed algorithm outperforms a standard detection algorithm specifically tailored to the analysed scenario. A statistical analysis of the experimental data is also performed to validate the hypotheses used to derive the detection algorithm. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of retrieving optically active parameters of the water from multispectral remotely sensed data. We analyse the neural networks approach applied to the estimation of chlorophyll concentration in coastal waters (Case II Waters) and discuss the use of two types of networks: the Radial Basis Function neural network and Multilayer Perceptron. We present a brief summary concerning their architectures and training methods. For proving the concept we analyse the procedures and the performances on a simulated data set reproducing the data acquired from the MERIS (Medium Resolution Imaging Spectrometer), the multispectral sensor on board the ENVISAT satellite. The multispectral subsurface reflectance data have been generated by means of a three component ocean colour direct model and statistically reproduce the case II waters. The neural networks performances have been analysed in terms of MSE (Mean Square Error), correlation coefficient and relative error. We provide a detailed discussion and comparison of the two types of networks and the obtained results confirm the effectiveness of the neural approach in such an application. [ABSTRACT FROM AUTHOR]

In 6H- or 4H-SiC(0001) surface technology, a Si-rich 3 x 3 reconstruction is usually first prepared by heating at 800°C under Si flux, and two other most stable √3 × √3 R30° or 6√3 × 6√3 R30° reconstructions are obtained by further extensive annealing at higher temperatures ranging between 900 and 1250°C. The 3 × 3 Si excess is thus progressively depleted up to a graphitized C-rich surface. By crystallographic (LEED) and chemical surface characterizations (XPS and UPS), we show that all these reconstructions can be obtained at a unique, low formation temperature of 800°C if the Si richness is controlled before annealing. This control is achieved by exposing the 3 × 3 surface to atomic hydrogen at room temperature. This procedure allows one to etch or partially deplete the (3 × 3)-associated Si excess, and make it more comparable to the final Si coverages, required to form the less Si-rich √3 × √3 R30° or 6√3 × 6√3 R30° reconstructions. After annealing at 800°C, the latter reconstructions are no longer determined by the heating time or temperature but only by the initial Si coverage set by the H doses inducing the low temperature etching. The high temperature treatment, required to remove by sublimation a significant Si amount associated with the Si-rich 3 × 3 reconstruction, is thus avoided. Such a methodology could be applied to other binary systems in the formation of reconstructions that depends on surface richness. [ABSTRACT FROM AUTHOR]

3C–SiC epitaxial crystal growth was carried out by repeated cycles of Si MBE deposition at room temperature followed by a carbonization under C2H4 and annealing at 900°C. This was done on a 3×3 reconstructed, well oriented, Si terminated 6H–SiC face. The surface was chemically and crystallographically controlled in situ by photoemission and LEED both during the cleaning procedure and within any growth sequence. By X-ray photoelectron diffraction and by transmission electron microscopy and diffraction, the 16 nm formed epilayer was characterized as a single 3C–SiC phase. A significant part of the cross-section image exhibits moire´ fringes whose periodicity (7.5 A˚) is three time the d1 1 1 reticular distance of the 3C–SiC monocrystal. This is attributed to the superimposition of {1 1 1} twinned domains, a consequence of two equiprobable orientation possibilities for 3C growth onto the hexagonal substrate. The formations of the 15R or the hypothetical 9R polytypes could be ruled out thanks to the electron diffraction patterns. [Copyright &y& Elsevier]

Investigates the effects of specular multipath on the reconstruction of high resolution target image provided by an inverse synthetic aperture radar (ISAR). Methodology used in study; Evaluation of the impulse response of the image system; Outline of the steps of the ISAR technique; Conclusion to study.

The LMS-based adaptive non-uniformity correction (NUC) technique, known in the literature as Scribner's algorithm, is an efficient method to mitigate the presence of fixed pattern noise in video sequences acquired by thermal cameras. Unfortunately, ghosting artefacts can be generated from the process of NUC depending on the edges that characterise the scene inside the sensor's field of view. Introduced is a de-ghosting technique based on the computation of the statistics of the error signal employed in the Scribner's algorithm. Such a technique is characterised by a small computational load which is the most important requirement for real-time applications. Experimental results demonstrate its good performance and de-ghosting capabilities. [ABSTRACT FROM AUTHOR]

Cerium oxide nanostructured thin films, as well as their variants doped with Gadolinium (Gd), Neodymium (Nd) and Indium (In), were successfully deposited onto both glass and ITO substrates using the spray pyrolysis method. Their structural, morphological, optical, and electrochemical properties were then experimentally studied. X-ray diffraction (XRD) has confirmed the generation of a single-phase polycrystalline cubic fluorite structure of CeO 2. The crystallite size and microstrain of the thin films were found to depend on the type of doping element. Red-shift, peak broadening, and asymmetry in the Raman mode (F 2g), as well as a red-shifted energy gap, were confirmed through Raman spectroscopy and UV–Vis–NIR analyses. SEM images reveal nanograin formation in all the films, while EDS analysis confirms the presence of the elements. The electrochemical measurements indicate that doping CeO 2 with Gd, Nd, and In enhances its electrochemical properties. Furthermore, the doped CeO 2 thin films maintain full transparency during the intercalation and deintercalation of Li + ions. Such pivotal findings broaden the potential applications of this oxide, particularly in supercapacitors and electrochromic devices. [ABSTRACT FROM AUTHOR]

In this study, the authors investigated the influence of hafnium doping on the properties of NiO thin films using the spray pyrolysis (SP) method. A comprehensive analysis was conducted to evaluate the structural, morphological, optical, and electrochemical characteristics of the deposited films. Techniques such as X-ray diffraction analysis (XRD), Raman spectroscopy, scanning electron microscopy (FESEM), energy dispersive analysis by X-ray (EDS), UV–Vis–NIR spectrophotometry, cyclic voltammetry (CV), and chronoamperometry (CA) were employed. XRD examination revealed that the NiO thin films exhibit a polycrystalline cubic phase, with a preferred orientation along the (111) plane. The successful integration of Hf ions into the NiO matrix was confirmed by the Raman spectrum. SEM images depicted the formation of dense and uniform nanograins on all film surfaces, free from any cracks. EDS analysis and elemental mapping indicated uniform and homogeneous distribution of Ni, O, and Hf elements across the films. The optical analysis suggested a decrease in the optical band gap energy from 3.54 eV to 3.49 eV with an increase in hafnium doping concentration. Electrochemical results revealed a continuous improvement in specific capacitance with Hf doping. The NHf6 sample reached 65 F. g−1 at 5 mV s−1, compared to 46 F. g−1 at 5 mV s−1 for the NHf0 sample. However, the NHf4 film exhibited the highest optical density variation (49%), shortest response times (t b = 3.58 s, t c = 4.67 s), and the largest coloration efficiency (63.39 cm2/C), indicating enhanced electrochromic performance at this Hf doping rate. These findings suggest that Hf-doped NiO holds promise as a candidate for use as a counter-electrode in electrochromic devices. [Display omitted] • Hafnium doped into NiO using Spray pyrolysis. • ΔOD enhanced from 21% to 49% by Hf doping. • The shortest time responses are t b = 3.58s and t c = 4.67s. • The largest CE is 63.39 cm2/C for the 4 at.% doping film. [ABSTRACT FROM AUTHOR]

Infrared search and track (IRST) systems based on 3-D velocity filters are quite sensitive to the random motion that remains after egomotion compensation has occurred (jitter). These systems are designed to detect small targets at long range and they often employ track-before-detect (TBD) strategies to integrate the target signal along consecutive frames. Jitter causes frame misalignment and leads to a reduction of the detection performance. We analyze the effects of jitter on the false alarm and detection probabilities and on the detection range. The analytical expressions here derived are a valuable tool both in the analysis and synthesis of IRST systems based on 3-D velocity filters. [ABSTRACT FROM AUTHOR]

The problem of full pixel target detection (FPTD) in hyperspectral images assuming that the target spectral signature is known is considered. Most of the detection algorithms proposed in the literature for FPTD have been derived from the additive model (AM) assumption. Since the AM is not appropriate to describe the FPTD problem, we resort to the more realistic replacement target model (RTM). It exploits the fact that in FPTD problems the target completely fills the image pixel obscuring or replacing the background. The derivation of an RTM-based detection strategy is one of the original contributions of this work. It is assumed that both the background and the target classes are characterised by the Gaussian model and that the two classes share the same covariance matrix. Assuming that both the background mean vector and the covariance matrix are unknown, the fully adaptive detector (FAD) is derived. It is shown that the performances of the FAD in typical operating conditions can be approximated by those of the adaptive detector (AD) derived by assuming that the background mean vector is known. The AD is theoretically analysed, its performances are derived and its CFAR behaviour is demonstrated. It is also stated that, in practice, the AD design methodology can be adopted to design FAD automatic target detectors. This issue is proved by simulation in a case study in which the model parameters are estimated from a hyperspectral dataset acquired by the airborne visible/infrared imaging spectrometer (AVIRIS). [ABSTRACT FROM AUTHOR]

The initial Ge growth stages on a (√3×√3)R30°-reconstructed SiC(0001) surface (√3) have been studied using a complete set of surface techniques such as reflection high energy electron diffraction (RHEED), low energy electron diffraction (LEED), atomic force microscopy (AFM) and photoemission and compared with similar Si surface enrichments in place of Ge. The investigations essentially focus on the wetting growth-regimes that are favoured by the use of the √3 surface as a starting substrate, this surface being the closest to a smooth and ideally truncated Si-terminated face of hexagonal SiC(0001). Depending on temperature and Ge or Si coverages, varying surface organizations are obtained. They range from unorganized layer by layer growths to relaxed Ge(111) or Si(111) island growths, through intermediate attempts of coherent and strained Ge or Si surface layers, characterized by 4×4 and 3×3 surface reconstructions, respectively. RHEED intensity oscillation recordings, as a function of Ge or Si deposited amounts, have been particularly helpful to pinpoint the limited (by the high lattice mismatch) existence domains of these interesting coherent phases, either in terms of formation temperature or surface coverages. Prominently comparable data for these two Ge- and Si-related reconstructions allow us to propose an atomic model for the still unexplained Ge-4×4 one. It is based on a same local organization in trimer and ad-atom units for the Ge excess as admitted for the Si-excess of the 3×3 surface, the higher strain nevertheless favouring arrangements, for the Ge-units, in 4×4 arrays instead of 3×3 Si ones. Admitting such models, 1.25 and 1.44 monolayers of Ge and Si, should, respectively, be able to lie coherently on SiC, with respective lattice mismatches near 30% and 25%. The experimental RHEED-oscillations values are compatible with such theoretical ones. Moreover, these RHEED coverage determinations (for layer completion, for instance) inform us in turn about the initial Si richness of the starting √3 reconstruction and help us to discriminate between earlier contradictory atomic models proposed in the literature. [Copyright &y& Elsevier]

Presents a study which utilized the range instantaneous doppler technique for the high-resolution inverse synthetic aperture radar (ISAR) imaging of maneuvering targets. Definition of the ISAR received signal model; Procedures for image reconstruction through the range doppler technique; Performance analysis.

Large surface area, 3D structured transparent electrodes with effective light management capability may represent a key component in the development of new generation optoelectronic and energy harvesting devices. We present an approach to obtain forest-like nanoporous/hierarchical Al-doped ZnO conducting layers with tunable transparency and light scattering properties, by means of room temperature Pulsed Laser Deposition in a mixed Ar:O 2 atmosphere. The composition of the background atmosphere during deposition can be varied to modify stoichiometry-related defects, and therefore achieve control of electrical and optical properties, while the total background pressure controls the material morphology at the nano- and mesoscale and thus the light scattering properties. This approach allows tuning electrical resistivity over a very wide range (10 − 1 − 10 6 Ω cm), both in the in-plane and cross-plane directions. Optical transparency and haze can also be tuned by varying the stoichiometry and thickness of the nano-forests. [ABSTRACT FROM AUTHOR]

The differences in systemic T-cell responses between patients with psoriatic arthritis ( Ps A) and patients with cutaneous psoriasis ( Ps) are still largely unknown. To determine differential features that could be used to distinguish Ps A from Ps, we compared the cytokine secretion profile of circulating T cells in patients with Ps A, patients with cutaneous Ps and control subjects. We determined Th1, Th2 and Th17 cytokine secretion of anti- CD3-stimulated peripheral blood mononuclear cells ( PBMCs) using a cytokine bead array. Normality of data distribution was assessed by the Shapiro- Wilk test, and statistical significance was calculated by the Mann- Whitney test. Phenotypic characterization of circulating T cells was performed by fluorescence-activated cell sorting analysis. We found that the major systemic differences distinguishing Ps A from cutaneous Ps were the increased secretion of interleukin ( IL)-2 by α- CD3-stimulated PBMCs and a higher percentage of circulating CD3+ T cells expressing the proliferation marker CD71 in Ps A. These results indicate IL-2 as a possible biomarker of Ps A, and suggest a role of circulating T cells with high proliferative capacity in the pathogenesis of Ps A. [ABSTRACT FROM AUTHOR]

• CuI changes the α-sexithiophene (α−6T) structure from amorphous to crystalline phase. • CuI causes an important enhancements in the absorption of α−6T thin films. • CuI reduces the roughness of the α−6T and increases its hole mobility. • Efficiency enhancement of α−6T/Fullerene system using MoO 3 /CuI hole transporting layer. • MoO 3 /CuI increases the life time of the α−6T/Fullerene device. In this work, planar heterojunction organic photovoltaic cells (PHJ-OPVs) based on alpha-sexithiophene (α-6T) and fullerene active materials were investigated. We have studied the effect of the hole transporting layer (HTL) on the performances of the PHJ-OPVs. The studied HTLs are molybdenum trioxide (MoO 3), cuprous iodide CuI and MoO 3 coupled with CuI (MoO 3 /CuI). The PHJ-OPVs were fabricated using the thermal evaporation/sublimation technique. The experimental study shows that double HTL MoO 3 /CuI, using 1.5 nm of CuI thickness, improves significantly the efficiency of the PHJ-OPVs compared with those with single HTLs. This enhancement is due to the fact that MoO 3 contributes to the optimization of the holes collection and CuI causes significant influence on the nucleation and the growth of α-6T. CuI has led to spectacular modification of the structural properties of α-6T. When α-6T is deposited onto ITO/MoO 3 , the α-6T layers are amorphous, while they are crystallized into monoclinic crystalline structure with a laying down molecular orientation when they are deposited onto ITO/MoO 3 /CuI. The use of the double HTL and the optimization of the α-6T deposition parameters have led to an important improvement in the α-6T light absorption, roughness and the holes mobility. These findings participated in the significant enhancement of the PHJ-OPVs performances and their life time. [ABSTRACT FROM AUTHOR]

Abstract: Silicon substrates are often used to synthesize polycrystalline diamond films by microwave plasma assisted chemical vapour deposition technique (MPCVD). In the case of highly oriented diamond films, several steps are employed to carefully prepare the silicon surface (pre-treatment steps), to nucleate diamond crystals (nucleation step) and to thick the film (growth step). In this study, we characterize {100} silicon substrates and diamond released from its silicon substrate by electronic microscopies (TEM and SEM), by Atomic Force Microscopy (AFM) and by X-ray photoelectron spectroscopy (XPS), to follow the substrate transformations after each step, particularly the formation and the evolution of the silicon carbide and to characterise the diamond films grown on the carburised silicon. We show that according to the experimental conditions and the level of surface/gas contamination by carbon and silicon species, isolated islands or continuous β-SiC compound are formed over the silicon surface and can generate defects such as voids or strip structures that influence the subsequent diamond nucleation and growth. [Copyright &y& Elsevier]

Abstract: Reflection high-energy electron diffraction (RHEED) has been used to determine epitaxy relationships and in-plane orientations between Ge and SiC(0001). Three monolayers of Ge have been deposited at 500°C on a graphitized SiC (6√3 × 6√3)R30° reconstructed surface, this surface supporting epitaxial Ge island growth in a Volmer–Weber mode. Nucleation of relaxed Ge-islands gives rise to transmission electron diffraction patterns allowing to deduce that pure Ge grows according to only one epitaxy relationship Ge{111}//SiC(0001). These {111}-Ge-islands have two in-plane orientations, a preferential one, Ge〈-1-12〉//SiC〈1-100〉 and a minority one, Ge〈-1-12〉//SiC〈10-10〉, deduced one from the other by a 30° rotation around the 〈111〉-Ge (or [0001]-SiC) growth axis. Due to the three-fold symmetry of the {111}-Ge plane, each in-plane orientation is degenerated into two twin orientations, differing by a 180° angle around Ge〈111〉. [Copyright &y& Elsevier]

The Ge growth on SiC(0 0 0 1) follows a Stranski–Krastanov mode for Si-rich (3×3) and (√ of 3×√ of 3)R30° reconstructed surfaces. For Ge deposit in particular temperature conditions, a new (4×4) superstructure takes place and the reflection high energy electron diffraction (RHEED) specular spot intensity presents one oscillation proving a wetting layer formation. An island nucleation is then ascertained by the oscillation vanishing and by the appearance of a k⊥-modulated RHEED pattern. On the other hand, on a (6√ of 3×6√ of 3)R30° C-rich surface, a direct Ge island nucleation is observed from the first growth stage. Indeed, for 1 ML Ge, the RHEED diagram consists in spots and rings, and the atomic force microscopy analysis indicates a high density (∼8×1010 cm-2) of small islands (∅∼30 nm, h∼3 nm). The RHEED spot analysis shows a preferential epitaxial relationship with the substrate Ge(1 1 1)//SiC(0 0 0 1). The Ge–C bonding being energetically unfavourable, Ge tends to form islands immediately rather than wetting the graphite-terminated surface. The Ge growth mode on C-rich surface is thus of Volmer–Weber type. [Copyright &y& Elsevier]

With the aim of comparing initial Ge adsorption and desorption modes on different surface terminations of 4H–SiC(0 0 0 1) faces, 3 × 3, √3×√3R30° (R3) and 6√3×6√3R30° (6R3) reconstructions, of decreasing Si surface richness, have been prepared by standard surface preparation procedures. They are controlled by reflection high energy electron diffraction (RHEED), low energy electron diffraction and photoemission. One monolayer of Ge has been deposited similarly at room temperature on each of these three surfaces, followed by the same set of isochronal heatings at increasing temperatures up to complete Ge desorption. At each step of heating, the structural and chemical status of the Ge ad-layer has been probed. Marked differences between the Si- (3 × 3 and R3) and C-rich (6R3) terminations have been obtained. Ge wetting layers are only obtained up to 400 °C on 3 × 3 and R3 surfaces in the form of a 4 × 4 reconstruction. The wetting is more complete on the R3 surface, whose atomic structure is the closest to an ideally Si-terminated 1 × 1 SiC surface. At higher temperatures, the wetting layer stage transiets in Ge polycrystallites followed by the unexpected appearance on the 3 × 3 surface of a more ordered Si island structure. It denotes a Si clustering of the initial Si 3 × 3 excess, induced by the presence of Ge. A phase separation mechanism between Si and Ge prevails therefore over alloying by Ge supply onto a such Si-terminated 3 × 3 surface. Conversely, no wetting is obtained on the 6R3 surface and island formation of exclusively pure Ge takes place already at low temperature. These islands exhibit a better epitaxial relationship characterized by Ge(1 1 1)//SiC(0 0 0 1) and Ge〈1 1 −2〉//SiC〈1 −1 0 0〉, ascertained by a clear RHEED spot pattern. The absence of any Ge–C bond signature in the X-ray photoelectron spectroscopy Ge core lines indicates a dominant island nucleation on heterogeneous regions of the surface denuded by the 6R3 graphite pavings. Owing to the used annealing cycles, the deposited Ge amount desorbs on the three surfaces at differentiated temperatures ranging from 950 to 1200 °C. These differences probably reflect the varying morphologies formed at lower temperature on the different surfaces. Considering all these results, the use of imperfect 6R3 surfaces appears to be suited to promote the formation of pure and coherent Ge islands on SiC. [Copyright &y& Elsevier]

Introduction: Psoriasis is a chronic inflammatory skin disease affecting approximately 2% of the population. Important clinical benefits in the treatment of psoriasis have been obtained with TNF inhibitors, which have also contributed to the understanding of mechanisms involved in the disease pathogenesis. Despite the evidence that TNF-inhibitors block the inflammatory cascade and induce a decrease of Th17 responses in the psoriatic plaques, their primary mechanism of action in inhibiting the self-sustaining pathogenic cycle in psoriasis is not completely understood . In this study we want to identify the early key events for the resolution of inflammation in psoriatic skin lesions upon treatment with TNF inhibitors. Methods: We used a translational approach combining quantitative gene expression analysis, clinical parameter of disease severity (PASI) and immunofluorescence analysis on tissue sections. Punch biopsies were collected from lesional skin at baseline and after 4weeks of anti-TNF therapy (Etanercept, Infliximab or Adalimumab) and gene expression levels were evaluated by qRT-PCR performed by TaqMan Low Density Array (Human Immune Panel). The correlation between changes of gene expression in lesional skin and the decrease of PASI score after treatment was calculated with Spearman’s rank correlation test. Data were validated by immunofluorescence microscopy on skin biopsies collected at baseline and after anti-TNF therapy (4weeks). Results: We found that among genes down-modulated by TNF inhibitors, the ones that mostly associated with clinical remission were Ccr7, its ligand Ccl19 and dendritic cell maturation genes. Clinical remission was also associated with the decreased expression of T cell activation genes and Vegf. Importantly, the down-regulation of Ccr7 observed at 4weeks also correlated with the clinical remission occurring at later time points. Immunofluorescence microscopy on skin biopsies showed that reduction of CCR7+ cells and CCL19 was paralleled by disaggregation of the dermal lymphoid-like tissue in the psoriatic plaque. Conclusion: These data show that early critical events for psoriasis resolution induced by TNF-blockade are the inhibition of CCR7/CCL19 axis and the disaggregation of the lymphoid-like tissue in the upper derma. This strongly supports the role of dermal lymphoid aggregate formation mediated by CCR7/CCL19 interaction in the pathogenesis of psoriasis. [Copyright &y& Elsevier]

Abstract: Epitaxial Ge islands on a SiC(0001) substrate have been examined by reflection high-energy electron diffraction (RHEED). These islands have been obtained by depositing three monolayers of Ge at 500°C on a graphitized SiC (6√3×6√3)R30° reconstructed surface. This surface has been chosen for its ability to support epitaxial Ge island growth in a Volmer-Weber mode. The RHEED technique has allowed us to determine the epitaxy relationship and in-plane orientations between relaxed Ge and SiC(0001). Typical transmission electron diffraction patterns indicate that Ge grows according to only one epitaxy relationship Ge{111}||SiC(0001) that corresponds to two in-plane orientations, a preferential one and a minority one rotated by 30° around the growth 〈111〉-Ge (or [0001]-SiC) axis. Double spot RHEED patterns also point out a twinning for each in-plane orientation, a consequence of the three-fold order of the 〈111〉-Ge axis. [Copyright &y& Elsevier]