205 research outputs found
Fostering the consensus: a BERT-based Multi-label Text Classifier to support agreement in public design call for tenders
Effect of early stress on hippocampal gray matter is influenced by a functional polymorphism in EAAT2 in bipolar disorder
n/
People flow management in a healthcare facility through crowd simulation and agent-based modeling methods
BIM-GIS integration and crowd simulation for fire emergency management in a large diffused university
Graphene sustained nonlinear modes in dielectric waveguides
We discuss the existence of nonlinear modes sustained by graphene layers in dielectric waveguides. Taking advantage of the almost two dimensional nature of graphene, we introduce the nonlinear effect as a parameter in the continuity equations. We then apply our modeling to a simple slab waveguide to enlighten how graphene can be used to induce huge nonlinear phase shifts at easily accessible power levels
16S rRNA gene amplicons and taxonomic classification of oral microbiome
The term microbiota refers to a set of microorganisms, considered as a living ecosystem, undergoing continuous changes in the growth and survival of all its members. The microbiome consists of the set of microorganism genomes. The human microbiota is estimated to contain about 10^14 commensal bacterial cells. The present high-throughput sequencing technology has led to the development of genome-based methods for bacterial classification and for understanding the functional role of the microbiota and its interaction with the host. In this study we explore the capability of a gene-based sequencing method to classify bacteria of the oral microbiome, the second largest microbial community in the human body, after the gut. The method depends on the detection of sequence variants in the bacterial 16S rRNA gene (length ~1500bp), present in all bacterial genomes. This gene includes nine hypervariable regions (V1-V9) that exhibit sequence diversity among different bacterial species. Therefore, the sequence variability of this gene is used to classify bacteria into proper taxonomic groups. The sequencing of one single hypervariable region cannot summarize the entire gene variability of the bacteria. Therefore, at least 2 hypervariable regions are generally studied. In gut studies the V3 and V4 regions are the most commonly analyzed. This could not be the case for oral microbiome studies. Here, we propose a study that investigates all the 9 hypervariable regions (6 amplicons) and how their characterization impacts on the overall taxa classification, at different taxonomic layers. This will permit to show up also the specificity of each hypervariable region (or their combination) to identify bacterial species. We collected 4 buccal swab samples from healthy individuals, and the extracted DNA was sequenced according to the QIAseq 16S/ITS panel handbook on an Illumina MiSeq NGS platform producing ~200,000 paired end reads (276PE) per sample. We carried out the study in two different ways: 1) by combining data from all amplicons of the 16S regions together, 2) by combining data from each amplicon region that was processed individually, in each sample. Amplicon analyses were performed using the Divisive Amplicon Denoising Algorithm (DADA2) that counts the number of amplicon sequence variants (ASVs) in each analyzed sample, reporting their abundance. ASVs were then classified using a pre-trained set for oral bacterial genome sequences (Human Oral Microbiome Database, version 15.1), slightly modified according to DADA2 requirements. The classification efficiency and accuracy (at genus or species layer) of every ASVs belonging to the different hypervariable regions was then ascertained. This analysis highlights the hypervariable regions able to capture the greatest gene variability for oral microbiome. Moreover, the ten most common species of each of the 6 amplicons, were reported for comparison purposes. We identified about 90 genera and more than 200 species; out of 9 identified phyla, Proteobacteria resulted to be the most abundant phylum (~ 56%). Of all the 2600 unique observed ASVs (4 samples), 1147 were successfully classified at the species taxonomic layer (overall classification rate: 44.1%). Overall, 204 different species were recognized with the entire set of combined amplicons, whereas 206 different species were identified by the combined results of single amplicons. The V1-V2 and V2-V3 amplicons recognized the highest number of species compared to the others, about 134 and 135 different species, respectively, of which 101 species in common. All the single regions showed almost the same ten most recurrent species. Moreover, each region resulted to be able to detect specific bacterial species that were not detectable by the other 16S regions. In conclusion, studying all the 9 16S gene regions is ~1.7 times more informative than studying just either one or 2 regions, and some species can be recognized only when studying specific regions. Still it remains doubtful how to treat data from different regions together to estimate the relative abundances of bacterial species within each sample
Modeling of enhanced field confinement and scattering by optical wire antennas.
We describe the application of full-wave and semi-analytical numerical tools for the modeling of optical wire antennas, with the aim of providing novel guidelines for analysis and design. The concept of antenna impedance at optical frequencies is reviewed by means of finite-element simulations, whereas a surface-impedance integral equation is derived in order to perform an accurate and efficient calculation of the current distribution, and thereby to determine the equivalent-circuit parameters. These are introduced into simple circuits models, directly borrowed from radio frequency, which are applied in order to model the phenomena of enhanced field confinement at the feed gap and light scattering by optical antennas illuminated by plane waves
Optical filter based on two coupled PhC GaAs-membranes.
We demonstrate an ultracompact optical filter based on two coupled high-index contrast GaAs photonic crystal (PhC) membranes. The PhC membranes consist of a square lattice of air holes and behave as a Fabry-Perot cavity whose reflectivity and transmissivity depend on the air gap between the two membranes. The normal-incidence reflectance measurements and the numerical simulation of reflection spectra show a high sensitivity to the geometrical parameters, such as the distance between the slabs, whose control would make the device suitable for a new class of tunable optical filters
Optical filter based on a coupled bilayer photonic crystal
We report on the fabrication of an ultra-compact optical filter based on photonic crystal free-standing membranes in bi-layer configuration. The basic heterostructure consists of two 376nm-thick GaAs-membranes sandwiched between air on a GaAs substrate. The air gap between the two membranes is 520nm thick. The normal-incidence reflectance measurements and the numerical simulation of reflection spectra show a high sensitivity to the holes diameter
- …