Interaction of Wind-Waves and Currents in Estuaries With Focus on Climate Change

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Disorder-driven electronic localization and phase separation in superconducting Fe1+yTe0.5Se0.5 single crystals

We have investigated the influence of Fe-excess on the electrical transport and magnetism of Fe1+yTe0.5Se0.5 (y=0.04 and 0.09) single crystals. Both compositions exhibit resistively determined superconducting transitions (Tc) with an onset temperature of about 15 K. From the width of the superconducting transition and the magnitude of the lower critical field Hc1, it is inferred that excess of Fe suppresses superconductivity. The linear and non-linear responses of the ac-susceptibility show that the superconducting state for these compositions is inhomogeneous. A possible origin of this phase separation is a magnetic coupling between Fe-excess occupying interstitial sites in the chalcogen planes and those in the Fe-square lattice. The temperature derivative of the resistivity drho/dT in the temperature range Tc < T < Ta with Ta being the temperature of a magnetic anomaly, changes from positive to negative with increasing Fe. A log 1/T divergence of the resistivity above Tc in the sample with higher amount of Fe suggests a disorder driven electronic localization.Comment: 7 page

Uncertainty-Aware Organ Classification for Surgical Data Science Applications in Laparoscopy

Objective: Surgical data science is evolving into a research field that aims to observe everything occurring within and around the treatment process to provide situation-aware data-driven assistance. In the context of endoscopic video analysis, the accurate classification of organs in the field of view of the camera proffers a technical challenge. Herein, we propose a new approach to anatomical structure classification and image tagging that features an intrinsic measure of confidence to estimate its own performance with high reliability and which can be applied to both RGB and multispectral imaging (MI) data. Methods: Organ recognition is performed using a superpixel classification strategy based on textural and reflectance information. Classification confidence is estimated by analyzing the dispersion of class probabilities. Assessment of the proposed technology is performed through a comprehensive in vivo study with seven pigs. Results: When applied to image tagging, mean accuracy in our experiments increased from 65% (RGB) and 80% (MI) to 90% (RGB) and 96% (MI) with the confidence measure. Conclusion: Results showed that the confidence measure had a significant influence on the classification accuracy, and MI data are better suited for anatomical structure labeling than RGB data. Significance: This work significantly enhances the state of art in automatic labeling of endoscopic videos by introducing the use of the confidence metric, and by being the first study to use MI data for in vivo laparoscopic tissue classification. The data of our experiments will be released as the first in vivo MI dataset upon publication of this paper.Comment: 7 pages, 6 images, 2 table

Scaling and Further Tests of Heavy Meson Decay Constant Determinations from Nonrelativistic QCD

We present results for the B_s meson decay constant f_{B_s} from simulations at three lattice spacings in the range a^{-1}=1.1 to 2.6 GeV using NRQCD heavy quarks and clover light quarks in the quenched approximation. We study scaling of this quantity and check the consistency between mesons decaying from rest and from a state with nonzero spatial momentum. The cancellation of power law contributions that arise in the NRQCD formulation of heavy-light currents is discussed. On the coarsest lattice the D_s meson decay constant f_{D_s} is calculated. Our best values for the decay constants are given by f_{B_s} = 187(4)(4)(11)(2)(7)(6) MeV and f_{D_s} = 223(6)(31)(38)(23)(9)(^{+3}_{-1}) MeV.Comment: 29 pages with 7 postscript figures, improved error analysis, version to appear in Physical Review

Recent developments in the characterization of superconducting films by microwaves

We describe and analyze selected surface impedance data recently obtained by different groups on cuprate, ruthenate and diboride superconducting films on metallic and dielectric substrates for fundamental studies and microwave applications. The discussion includes a first review of microwave data on MgB2, the weak-link behaviour of RABiTS-type YBa2Cu3O7-d tapes, and the observation of a strong anomalous power-dependence of the microwave losses in MgO at low temperatures. We demonstrate how microwave measurements can be used to investigate electronic, magnetic, and dielectric dissipation and relaxation in the films and substrates. The impact of such studies reaches from the extraction of microscopic information to the engineering of materials and further on to applications in power systems and communication technology.Comment: Invited contribution to EUCAS2001, accepted for publication in Physica C in its present for

Physiological parameter estimation from multispectral images unleashed

Multispectral imaging in laparoscopy can provide tissue reflectance measurements for each point in the image at multiple wavelengths of light. These reflectances encode information on important physiological parameters not visible to the naked eye. Fast decoding of the data during surgery, however, remains challenging. While model-based methods suffer from inaccurate base assumptions, a major bottleneck related to competing machine learning-based solutions is the lack of labelled training data. In this paper, we address this issue with the first transfer learning-based method to physiological parameter estimation from multispectral images. It relies on a highly generic tissue model that aims to capture the full range of optical tissue parameters that can potentially be observed in vivo. Adaptation of the model to a specific clinical application based on unlabelled in vivo data is achieved using a new concept of domain adaptation that explicitly addresses the high variance often introduced by conventional covariance-shift correction methods. According to comprehensive in silico and in vivo experiments our approach enables accurate parameter estimation for various tissue types without the need for incorporating specific prior knowledge on optical properties and could thus pave the way for many exciting applications in multispectral laparoscopy