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A mental and physical recovery after an awakening moment depends not only on the overall sleep duration and quality but mostly on the sleep stage in the waking moment. The most comfortable awakening moment is during the Light or Wake sleep stages. But the fix-time alarm clock doesn't take into account the sleep stage in the awakening moment, which often results in awakening during the Deep or Rapid Eyes Movement stages. To reduce the negative recovery effect, big companies and research groups develop various awakening systems. Such systems recognize sleep stages based on wearable sensors' data (mostly from accelerometer sensors) and thus can find the easiest awakening moment time with minimal recovery effects.However, it is quite hard to measure and verify the efficiency of such systems without using polysomnography (which can be performed only in clinical conditions by medical experts). To solve this problem we developed a methodology based on questionnaires and psychological tests. Such an approach has big scalability, does not require special medical equipment, and can be evaluated in a home environment with minimal support effort. The proposed verification approach has been tested on smartwatches with the sleep stages forecast model. The proposed model accuracy was 78%. Results of our experiment show that the majority of users demonstrated a correlation between awakening quality and the verification tests performance.

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Recently, mobile and wearable devices have become an increasingly integral part of our lives. They provide a possibility of detailed health monitoring using noninvasive and user-friendly techniques. However, lack of continuous monitoring, the need of specific sensors, and the limitations in memory and power consumption are only some of the potential drawbacks of such devices. In the current paper a system based on a deep recurrent neural network is developed for an automatic continuous monitoring of sleep-related physiological parameters by means of a wearable biosignal monitoring systems. Smartwatches based algorithm for non-invasive monitoring of sleep stages, respiratory events (including sleep apnea and hypopnea), snore and blood oxygen saturation is developed. Our experimental results demonstrate that proposed model constitutes a noninvasive and inexpensive screening system for sleep-related physiological parameters and pathological states. The model has shown a 77 % accuracy in sleep stages prediction, more than 80 % accuracy in epoch-by-epoch respiratory events classification, above 60 % accuracy in snore events classification and above 70 % accuracy in blood oxygen saturation (SpO2) level classification (for a two class problem with a SpO2 threshold of 95 %).

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A sleep inertia after waking up strongly affects the overall mental recovery after sleep. The sleep inertia depends not as much on overall sleep quality but also on the sleep stage in the waking up moment. The fix-time alarming system results in waking up at random sleep stage, which results in frequent sleep inertia. The widely used flow-time alarming systems based on motion detection (actigraphy) reduce but do not eliminate sleep inertia. Such systems do not wake up users in Deep sleep stage, but may instead wake them up in Wake, Light, or REM (Rapid Eyes Movement) stages. Moreover, frequent waking up in the REM stage results in serious psychological issues. We present a smartwatch alarm system that predicts sleep stages and thus produces an alarm call at an easy waking up moment with minimal sleep inertia effect. The sleep stages are predicted using an Encoder-Decoder Recurrent Neural Network model. The rationale of the prediction is that each sleep stages cycling pattern is a continuous quasi-periodic process. Experimental results from over 138 nocturnal sleep periods from 92 respondents show that our system provides 66-70% accuracy for Deep, Light, Wake, REM sleep stages and 71-77% accuracy for 2-classes (Deep/REM vs. Light/Wake stages) prediction classifications. The proposed alarm system wakes up the user at the moment when Easy Wake (Wake/Light) stage is the most probable.

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The formation of a macroscopic cholesteric spiral in a nematic liquid crystal (LC) doped with chiral molecules is studied. Measurements of the orientation of the disclination line formed in a LC θ-cell manufactured with one substrate having linear in-plane alignment and the opposing substrate having circular alignment showed the formation of a uniform macroscopic cholesteric spiral with a pitch length of centimeters. We found a linear dependence of the reciprocal pitch p(-1) on the concentration c in a wide range of p, extending from micrometers up to several centimeters. It suggests that the pitch of a spiral in a nematic LC doped with chiral dopants results from a long-range orientation owing to short-range chiral interactions in the vicinity of the chiral additive.

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UV-Vis absorption spectroscopy is frequently used to characterize the size and shape of gold nanoparticles. We present a full-spectrum model that yields reliable results for the commonly encountered case of mixtures of spheres and rods in varying proportions. We determine the volume fractions of the two populations, the aspect ratio distribution of the nanorods (average value and variance) and the interface damping parameter. We validate the model by checking the fit results against small-angle X-ray scattering and transmission electron microscopy data and show that correctly accounting for the polydispersity in aspect ratio is essential for a quantitative description of the longitudinal plasmon peak.

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We report a hybrid mesophase consisting of magnetic nanorods confined between the non-ionic surfactant bilayers of a lamellar phase. The magnetic field-induced ordering of the nanorods was measured experimentally and modeled by a two-dimensional Onsager theory including the third virial coefficient. The nanorods are strongly confined in layers, with no orientational coupling from one layer to the next. At high volume concentration they exhibit spontaneous in-plane orientational ordering and form a stack of independent two-dimensional nematic systems. This isotropic-nematic transition is first-order.

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Polarization gratings have been recorded in a combined liquid crystal (LC) cell made of a substrate covered with a photosensitive chalcogenide orientation layer and a reference substrate covered with a rubbed polyimide film. The gratings are formed due to the spatially modulated light-induced easy orientation axis on the chalcogenide surface recorded by two beams with opposite circular polarizations. The gratings are permanent, but they can be erased by one of the recording beams and re-recorded. The diffraction intensity of the circularly polarized light is achromatic and does not depend on the birefringence of the LC. The diffraction efficiency of the grating is of the order of a few percents. Application of an ac field causes a strong increase of the diffraction efficiency up to 45%.

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We present in this Rapid Communication experimental evidence of an acceleration of the zenithal easy-axis dynamics of a nematic liquid crystal (NLC) with the age of a NLC-polymer layer. The comparison with other hard alignment layers strongly indicates that the polymer softness and its ability to reorient in the nematic ordering field is at the origin of the measured dynamics. The unusual acceleration of the dynamics with the polymer age is discussed in terms of this unique coupling with the NLC order. The NLC behaves like a physical plasticizer as a result of the coupling between the NLC and the polymer orders.

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We studied the effect of light-induced gliding of the easy axis of dye-doped nematic liquid crystal on an aligning polymer surface. The observed drift of the easy axis is over tens of degrees and is caused by light-induced anisotropic adsorption and/or desorption of dye molecules on or from the aligning layer in the presence of light-induced bulk torque. We present a theoretical model that explains the experimental data in terms of the light-induced changes of the adsorbed dye molecules angular distribution due to their exchange with the dye molecules from the liquid crystal bulk.