Automatic sleep staging of EEG signals: recent development, challenges, and future directions.

Modern deep learning holds a great potential to transform clinical studies of human sleep. Teaching a machine to carry out routine tasks would be a tremendous reduction in workload for clinicians. Sleep staging, a fundamental step in sleep practice, is a suitable task for this and will be the focus in this article. Recently, automatic sleep-staging systems have been trained to mimic manual scoring, leading to similar performance to human sleep experts, at least on scoring of healthy subjects. Despite tremendous progress, we have not seen automatic sleep scoring adopted widely in clinical environments. This review aims to provide the shared view of the authors on the most recent state-of-the-art developments in automatic sleep staging, the challenges that still need to be addressed, and the future directions needed for automatic sleep scoring to achieve clinical value

Metallic characteristics in superlattices composed of insulators, NdMnO3/SrMnO3/LaMnO3

We report on the electronic properties of superlattices composed of three different antiferromagnetic insulators, NdMnO3/SrMnO3/LaMnO3 grown on SrTiO3 substrates. Photoemission spectra obtained by tuning the x-ray energy at the Mn 2p -> 3d edge show a Fermi cut-off, indicating metallic behavior mainly originating from Mn e_g electrons. Furthermore, the density of states near the Fermi energy and the magnetization obey a similar temperature dependence, suggesting a correlation between the spin and charge degrees of freedom at the interfaces of these oxides

Catalytic pyrolysis of plastic waste using metal-incorporated activated carbons for monomer recovery and carbon nanotube synthesis

As the global plastic waste crisis intensifies, innovative and sustainable solutions are urgently needed. This study evaluated waste-derived metal-incorporated activated carbon (AC) catalysts for the pyrolysis of mixed plastic waste to generate value-added products, focusing on product yield distribution, composition, hydrogen, and carbon nanotube (CNT) formation. Pyrolysis-catalysis experiments were conducted using a two-stage fixed-bed reactor, wherein the temperature was maintained at 500 °C in first stage (pyrolysis) and varied (500, 600, and 700 °C) in the second stage (catalysis). The tested ACs were incorporated with nickel (Ni-AC), iron (Fe-AC), and zinc (Zn-AC) to assess the impact of metal particles distributed on the carbonaceous support in the second stage. The results from the ACs were compared to those obtained using zeolite (H-ZSM-5), Raw-AC, and non-catalytic runs. The Ni-AC and Fe-AC demonstrated superior catalytic activity, with Ni-AC being more efficient in producing hydrogen (4.24wt%) and CNTs (34.5wt%) with diameters of approximately 30nm, and Fe-AC leading to higher gas yields (68.8wt%) and CNTs (12.4wt%) of around 60nm. In contrast, Zn-AC and Raw-AC presented limited effectiveness, although Raw-AC moderately outperformed Zn-AC with enhanced gas yields and reduced oil/wax yields. The zeolite H-ZSM-5 exhibited the highest gas yields (78wt%), converting heavy fractions into lighter molecules, notably the monomers ethylene and propylene. These findings provide valuable insights into catalyst selection and optimization for plastic waste pyrolysis processes, with H-ZSM-5 being the most effective catalyst for monomer recovery, and Ni-AC and Fe-AC demonstrating promising results

Magnetic Reconnection and Intermittent Turbulence in the Solar Wind

A statistical relationship between magnetic reconnection, current sheets and intermittent turbulence in the solar wind is reported for the first time using in-situ measurements from the Wind spacecraft at 1 AU. We identify intermittency as non-Gaussian fluctuations in increments of the magnetic field vector, $\mathbf{B}$, that are spatially and temporally non-uniform. The reconnection events and current sheets are found to be concentrated in intervals of intermittent turbulence, identified using the partial variance of increments method: within the most non-Gaussian 1% of fluctuations in $\mathbf{B}$, we find 87%-92% of reconnection exhausts and $\sim$9% of current sheets. Also, the likelihood that an identified current sheet will also correspond to a reconnection exhaust increases dramatically as the least intermittent fluctuations are removed from the dataset. Hence, the turbulent solar wind contains a hierarchy of intermittent magnetic field structures that are increasingly linked to current sheets, which in turn are progressively more likely to correspond to sites of magnetic reconnection. These results could have far reaching implications for laboratory and astrophysical plasmas where turbulence and magnetic reconnection are ubiquitous.Comment: 5 pages, 3 figures, submitted to Physical Review Letter

Sleep monitoring using ear-centered setups: Investigating the influence from electrode configurations.

Modern sleep monitoring development is shifting towards the use of unobtrusive sensors combined with algorithms for automatic sleep scoring. Many different combinations of wet and dry electrodes, ear-centered, forehead-mounted or headband-inspired designs have been proposed, alongside an ever growing variety of machine learning algorithms for automatic sleep scoring. OBJECTIVE: Among candidate positions, those in the facial area and around the ears have the benefit of being relatively hairless, and in our view deserve extra attention. In this paper, we seek to determine the limits to sleep monitoring quality within this spatial constraint. METHODS: We compare 13 different, realistic sensor setups derived from the same data set and analysed with the same pipeline. RESULTS: All setups which include both a lateral and an EOG derivation show similar, state-of-the-art performance, with average Cohen's kappa values of at least 0.80. CONCLUSION: If large electrode distances are used, positioning is not critical for achieving large sleep-related signal-to-noise-ratio, and hence accurate sleep scoring. SIGNIFICANCE: We argue that with the current competitive performance of automated staging approaches, there is a need for establishing an improved benchmark beyond current single human rater scoring

Inverse lift: a signature of the elasticity of complex fluids?

To understand the mechanics of a complex fluid such as a foam we propose a model experiment (a bidimensional flow around an obstacle) for which an external sollicitation is applied, and a local response is measured, simultaneously. We observe that an asymmetric obstacle (cambered airfoil profile) experiences a downards lift, opposite to the lift usually known (in a different context) in aerodynamics. Correlations of velocity, deformations and pressure fields yield a clear explanation of this inverse lift, involving the elasticity of the foam. We argue that such an inverse lift is likely common to complex fluids with elasticity.Comment: 4 pages, 4 figures, revised version, submitted to PR