Search results for "STED"
showing 10 items of 2256 documents
Splitting of surface-related phonons in Raman spectra of self-assembled GaN nanowires
2012
cited By 2; International audience; Micro Raman spectroscopy studies have been performed on GaN nanowires grown by Plasma-Assisted Molecular Beam Epitaxy on Silicon (111) substrate. From the analysis of experimental data, the emergence of a two peaks band located near 700 cm-1 has been attributed to the Raman scattering by surface-related phonons. We have analyzed the surface character of these two modes by changing the dielectric constant of the exterior medium and some experimental parameters. Furthermore, a theoretical model describing the nanowires ensemble by means of an effective dielectric function has been used to interpret the Raman scattering results. Those numerical simulations a…
Combined effects of compost and Medicago sativa in recovery a PCB contaminated soil
2020
The effectiveness of adding compost and the plant Medicago sativa in improving the quality of a soil historically contaminated by polychlorinated biphenyls (PCBs) was tested in greenhouse microcosms. Plant pots, containing soil samples from an area contaminated by PCBs, were treated with the compost and the plant, separately or together. Moreover, un-treated and un-planted microcosms were used as controls. At fixed times (1, 133 and 224 days), PCBs were analysed and the structure (cell abundance, phylogenetic characterization) and functioning (cell viability, dehydrogenase activity) of the natural microbial community were also measured. The results showed the effectiveness of the compost an…
Learning With Context Feedback Loop for Robust Medical Image Segmentation
2021
Deep learning has successfully been leveraged for medical image segmentation. It employs convolutional neural networks (CNN) to learn distinctive image features from a defined pixel-wise objective function. However, this approach can lead to less output pixel interdependence producing incomplete and unrealistic segmentation results. In this paper, we present a fully automatic deep learning method for robust medical image segmentation by formulating the segmentation problem as a recurrent framework using two systems. The first one is a forward system of an encoder-decoder CNN that predicts the segmentation result from the input image. The predicted probabilistic output of the forward system …
Deep neural networks to recover unknown physical parameters from oscillating time series.
2022
PLOS ONE 17(5), e0268439 (2022). doi:10.1371/journal.pone.0268439
Mahonian STAT on rearrangement class of words
2017
In 2000, Babson and Steingr\'{i}msson generalized the notion of permutation patterns to the so-called vincular patterns, and they showed that many Mahonian statistics can be expressed as sums of vincular pattern occurrence statistics. STAT is one of such Mahonian statistics discoverd by them. In 2016, Kitaev and the third author introduced a words analogue of STAT and proved a joint equidistribution result involving two sextuple statistics on the whole set of words with fixed length and alphabet. Moreover, their computer experiments hinted at a finer involution on $R(w)$, the rearrangement class of a given word $w$. We construct such an involution in this paper, which yields a comparable jo…
Classical automata on promise problems
2015
Promise problems were mainly studied in quantum automata theory. Here we focus on state complexity of classical automata for promise problems. First, it was known that there is a family of unary promise problems solvable by quantum automata by using a single qubit, but the number of states required by corresponding one-way deterministic automata cannot be bounded by a constant. For this family, we show that even two-way nondeterminism does not help to save a single state. By comparing this with the corresponding state complexity of alternating machines, we then get a tight exponential gap between two-way nondeterministic and one-way alternating automata solving unary promise problems. Secon…
Bayesian Analysis of Population Health Data
2021
The analysis of population-wide datasets can provide insight on the health status of large populations so that public health officials can make data-driven decisions. The analysis of such datasets often requires highly parameterized models with different types of fixed and random effects to account for risk factors, spatial and temporal variations, multilevel effects and other sources on uncertainty. To illustrate the potential of Bayesian hierarchical models, a dataset of about 500,000 inhabitants released by the Polish National Health Fund containing information about ischemic stroke incidence for a 2-year period is analyzed using different types of models. Spatial logistic regression and…
Fast Estimation of Diffusion Tensors under Rician noise by the EM algorithm
2016
Diffusion tensor imaging (DTI) is widely used to characterize, in vivo, the white matter of the central nerve system (CNS). This biological tissue contains much anatomic, structural and orientational information of fibers in human brain. Spectral data from the displacement distribution of water molecules located in the brain tissue are collected by a magnetic resonance scanner and acquired in the Fourier domain. After the Fourier inversion, the noise distribution is Gaussian in both real and imaginary parts and, as a consequence, the recorded magnitude data are corrupted by Rician noise. Statistical estimation of diffusion leads a non-linear regression problem. In this paper, we present a f…
ECOLOGICAL FEATURES OF MACROMYCETES IN EUCALYPTUS REFORESTATIONS IN SICILY (SOUTHERN ITALY)
2009
The objective of this work was to compare and estimate the ecological features of 192 macromycetes, including nine hypogeous and three semi-hypogeous fungi, collected in Sicilian areas reforested with Eucalyptus. The number of mycorrhizal fungi turned out to be only 22 % of the taxa recorded so far from other areas, and this underlines the difficulties of eucalyptus trees in adapting to the pedological and climatic conditions of Sicily.
Label swapper device for spectral amplitude coded optical packet networks monolithically integrated on InP
2011
In this paper the design, fabrication and experimental characterization of an spectral amplitude coded (SAC) optical label swapper monolithically integrated on Indium Phosphide (InP) is presented. The device has a footprint of 4.8x1.5 mm 2 and is able to perform label swapping operations required in SAC at a speed of 155 Mbps. The device was manufactured in InP using a multiple purpose generic integration scheme. Compared to previous SAC label swapper demonstrations, using discrete component assembly, this label swapper chip operates two order of magnitudes faster. © 2011 Optical Society of America.