FUSE Detection of Galactic OVI Emission in the Halo above the Perseus Arm

Background observations obtained with the Far Ultraviolet Spectroscopic Explorer (FUSE) toward l=95.4, b=36.1 show OVI 1032,1038 in emission. This sight line probes a region of stronger-than-average soft X-ray emission in the direction of high-velocity cloud Complex C above a part of the disk where Halpha filaments rise into the halo. The OVI intensities, 1600+/-300 ph/s/cm^2/sr (1032A) and 800+/-300 ph/s/cm^2/sr (1038A), are the lowest detected in emission in the Milky Way to date. A second sight line nearby (l=99.3, b=43.3) also shows OVI 1032 emission, but with too low a signal-to-noise ratio to obtain reliable measurements. The measured intensities, velocities, and FWHMs of the OVI doublet and the CII* line at 1037A are consistent with a model in which the observed emission is produced in the Galactic halo by hot gas ejected by supernovae in the Perseus arm. An association of the observed gas with Complex C appears unlikely.Comment: accepted for publication in ApJL, 11 pages including 3 figure

Vibrationally Induced Two-Level Systems in Single-Molecule Junctions

Single-molecule junctions are found to show anomalous spikes in dI/dV spectra. The position in energy of the spikes are related to local vibration mode energies. A model of vibrationally induced two-level systems reproduces the data very well. This mechanism is expected to be quite general for single-molecule junctions. It acts as an intrinsic amplification mechanism for local vibration mode features and may be exploited as a new spectroscopic tool.Comment: 4 pages, 4 figure

Hierarchical Temporal Representation in Linear Reservoir Computing

Recently, studies on deep Reservoir Computing (RC) highlighted the role of layering in deep recurrent neural networks (RNNs). In this paper, the use of linear recurrent units allows us to bring more evidence on the intrinsic hierarchical temporal representation in deep RNNs through frequency analysis applied to the state signals. The potentiality of our approach is assessed on the class of Multiple Superimposed Oscillator tasks. Furthermore, our investigation provides useful insights to open a discussion on the main aspects that characterize the deep learning framework in the temporal domain.Comment: This is a pre-print of the paper submitted to the 27th Italian Workshop on Neural Networks, WIRN 201

Surface plasmon resonance biosensors for highly sensitive detection in real samples

In this work we summarize the main results obtained with the portable surface plasmon resonance (SPR) device developed in our group (commercialised by SENSIA, SL, Spain), highlighting its applicability for the real-time detection of extremely low concentrations of toxic pesticides in environmental water samples. In addition, we show applications in clinical diagnosis as, on the one hand, the real-time and label-free detection of DNA hybridization and single point mutations at the gene BRCA-1, related to the predisposition in women to develop an inherited breast cancer and, on the other hand, the analysis of protein biomarkers in biological samples (urine, serum) for early detection of diseases. Despite the large number of applications already proven, the SPR technology has two main drawbacks: (i) not enough sensitivity for some specific applications (where pM-fM or single-molecule detection are needed) (ii) low multiplexing capabilities. In order solve such drawbacks, we work in several alternative configurations as the Magneto-optical Surface Plasmon Resonance sensor (MOSPR) based on a combination of magnetooptical and ferromagnetic materials, to improve the SPR sensitivity, or the Localized Surface Plasmon Resonance (LSPR) based on nanostructures (nanoparticles, nanoholes,...), for higher multiplexing capabilities