The Dimer Model for k-phase Organic Superconductors

We prove that the upper electronic bands of k-phase BEDT-TTF salts are adequately modeled by an half-filled tight-binding lattice with one site per cell. The band parameters are derived from recent ab-initio calculations, getting a very simple but extremely accurate one-electron picture. This picture allows us to solve the BCS gap equation adopting a real-space pairing potential. Comparison of the calculated superconducting properties with the experimental data points to isotropic s_0-pairing. Residual many-body or phonon-mediated interactions offer a plausible explanation of the large variety of physical properties observed in k-phase BEDT-TTF salts.Comment: 8 pages, 6 PostScript figures, uses RevTe

Symmetrized mean-field description of magnetic instabilities in k-(BEDT-TTF)_2Cu[N(CN)]_2 Y salts

We present a novel and convenient mean-field method, and apply it to study the metallic/antiferromagnetic interface of k-(BEDT-TTF)_2Cu[N(CN)]_2 Y organic superconductors (BEDT_TTF is bis-ethylen-dithio-tetrathiafulvalene, Y=Cl, Br). The method, which fully exploits the crystal symmetry, allows one to obtain the mean-field solution of the 2D Hubbard model for very large lattices, up to 6x10^5 sites, yielding a reliable description of the phase boundary in a wide region of the parameter space. The metal/antiferromagnet transtion appears to be second order, except for a narrow region of the parameter space, where the transition is very sharp and possibly first order. The cohexistence of metallic and antiferromagnetic properties is only observed for the transient state in the case of smooth second order transitions. The relevance of the present resaults to the complex experimental behavior of centrosymmetric k-phase BEDT-TTF salts is discussed.Comment: 9 pages in PS format, 7 figures (included in PS), 1 tabl

Feature-based multi-class classification and novelty detection for fault diagnosis of industrial machinery

Given the strategic role that maintenance assumes in achieving profitability and competitiveness, many industries are dedicating many efforts and resources to improve their maintenance approaches. The concept of the Smart Factory and the possibility of highly connected plants enable the collection of massive data that allow equipment to be monitored continuously and real-time feedback on their health status. The main issue met by industries is the lack of data corresponding to faulty conditions, due to environmental and safety issues that failed machinery might cause, besides the production loss and product quality issues. In this paper, a complete and easy-to-implement procedure for streaming fault diagnosis and novelty detection, using different Machine Learning techniques, is applied to an industrial machinery sub-system. The paper aims to offer useful guidelines to practitioners to choose the best solution for their systems, including a model hyperparameter optimization technique that supports the choice of the best model. Results indicate that the methodology is easy, fast, and accurate. Few training data guarantee a high accuracy and a high generalization ability of the classification models, while the integration of a classifier and an anomaly detector reduces the number of false alarms and the computational time

BEDT-TTF organic superconductors: the entangled role of phonons

We calculate the lattice phonons and the electron-phonon coupling of the organic superconductor \kappa-(BEDT-TTF)_2 I_3, reproducing all available experimental data connected to phonon dynamics. Low-frequency intra-molecular vibrations are strongly mixed to lattice phonons. Both acoustic and optical phonons are appreciably coupled to electrons through the modulation of the hopping integrals (e-LP coupling). By comparing the results relevant to superconducting \kappa- and \beta-(BEDT-TTF)_2 I_3, we show that electron-phonon coupling is fundamental to the pairing mechanism. Both e-LP and electron-molecular vibration (e-MV) coupling are essential to reproduce the critical temperatures. The e-LP coupling is stronger, but e-MV is instrumental to increase the average phonon frequency.Comment: 4 pages, including 4 figures. Published version, with Ref. 17 corrected after publicatio

Flutuação populacional do ácaro-verde, Mononychellus planki, em soja safrinha.

O objetivo do presente trabalho foi realizar um levantamento para avaliar a flutuação populacional de ácaros associados com a soja safrinha cultivada em sucessão a soja e milho

Densidade de pragas e inimigos naturais em resposta ao tratamento de sementes de soja com inseticidas.

Objetivo: avaliar o efeito do tratamento de sementes de soja com inseticidas químicos sobre a frequência densidade populacional diária acumulada de insetos-praga e artrópodes predadores da parte aérea da soja ao longo do desenvolvimento da cultura

Diagnostic efficacy of the ELISA test for the detection of deamidated anti-gliadin peptide antibodies in the diagnosis and monitoring of celiac disease

Volcano plot of differential gene expression in IZE_Suc vs IZE, ZE_5w vs IZE_Suc and SE_5w vs IZE. (DOCX 256 kb

Towards a Computed-Aided Diagnosis System in Colonoscopy: Automatic Polyp Segmentation Using Convolution Neural Networks

Early diagnosis is essential for the successful treatment of bowel cancers including colorectal cancer (CRC), and capsule endoscopic imaging with robotic actuation can be a valuable diagnostic tool when combined with automated image analysis. We present a deep learning rooted detection and segmentation framework for recognizing lesions in colonoscopy and capsule endoscopy images. We restructure established convolution architectures, such as VGG and ResNets, by converting them into fully-connected convolution networks (FCNs), fine-tune them and study their capabilities for polyp segmentation and detection. We additionally use shape-from-shading (SfS) to recover depth and provide a richer representation of the tissue’s structure in colonoscopy images. Depth is incorporated into our network models as an additional input channel to the RGB information and we demonstrate that the resulting network yields improved performance. Our networks are tested on publicly available datasets and the most accurate segmentation model achieved a mean segmentation interception over union (IU) of 47.78% and 56.95% on the ETIS-Larib and CVC-Colon datasets, respectively. For polyp detection, the top performing models we propose surpass the current state-of-the-art with detection recalls superior to 90% for all datasets tested. To our knowledge, we present the first work to use FCNs for polyp segmentation in addition to proposing a novel combination of SfS and RGB that boosts performance

The largest prehistoric mound in Europe is the Bronze-Age Hill of Udine (Italy) and legend linked its origin to Attila the Hun

Prehistoric monuments often constitute evident landmarks and sometimes, after falling into disuse, fascinated local people enough to stimulate speculations about their origin over time. According to legend, the Hill of Udine (NE Italy) was built by Attila the Hun's soldiers, but its origin (natural or anthropogenic) has been debated until now. Our research analyzed five new 40-m long stratigraphic cores, investigating for the first time the total thickness of the hill and compared the data with the available archaeological information. Moreover, we considered other hills and mounds in northern Italy and other European regions where folklore traditions relate their origin to Attila. The geoarchaeological and ethnographic data prove that the Hill of Udine is a Bronze Age anthropogenic mound erected between 1400 and 1150 BCE and that, later, folklore has transformed the ancestral memory of its origin into legend. By measuring 30 m in height and over 400,000 m(3) in volume, the flat-topped hill is the largest prehistoric mound in Europe. This discovery reveals unprecedented skills in earth construction and confirms significant anthropogenic modifications of the environment during Bronze Age

Efeito da soja Bt sobre a frequência e densidade populacional de pragas e predadores.

Este trabalho tem por objetivo avaliar comparativamente a frequência e a densidade populacional acumulada de insetos fitófagos e de artrópodes predadores, em campos de soja não-transgênica, RR e Bt