Hidden semi-Markov Model based earthquake classification system using Weighted Finite-State Transducers

Automatic earthquake detection and classification is required for efficient analysis of large seismic datasets. Such techniques are particularly important now because access to measures of ground motion is nearly unlimited and the target waveforms (earthquakes) are often hard to detect and classify. Here, we propose to use models from speech synthesis which extend the double stochastic models from speech recognition by integrating a more realistic duration of the target waveforms. The method, which has general applicability, is applied to earthquake detection and classification. First, we generate characteristic functions from the time-series. The Hidden semi-Markov Models are estimated from the characteristic functions and Weighted Finite-State Transducers are constructed for the classification. We test our scheme on one month of continuous seismic data, which corresponds to 370 151 classifications, showing that incorporating the time dependency explicitly in the models significantly improves the results compared to Hidden Markov Models

Hall mobilities and sheet carrier densities in a single LiNbO3_3 conductive ferroelectric domain wall

For the last decade, conductive domain walls (CDWs) in single crystals of the uniaxial model ferroelectric lithium niobate (LiNbO$_3$, LNO) have shown to reach resistances more than 10 orders of magnitude lower as compared to the surrounding bulk, with charge carriers being firmly confined to sheets of a few nanometers in width. LNO thus currently witnesses an increased attention since bearing the potential for variably designing room-temperature nanoelectronic circuits and devices based on such CDWs. In this context, the reliable determination of the fundamental transport parameters of LNO CDWs, in particular the 2D charge carrier density $n_{2D}$ and the Hall mobility $\mu_{H}$ of the majority carriers, are of highest interest. In this contribution, we present and apply a robust and easy-to-prepare Hall-effect measurement setup by adapting the standard 4-probe van-der-Pauw method to contact a single, hexagonally-shaped domain wall that fully penetrates the 200-$\mu$m-thick LNO bulk single crystal. We then determine $n_{2D}$ and $\mu_{H}$ for a set of external magnetic fields $B$ and prove the expected cosine-like angular dependence of the Hall voltage. Lastly, we present photo-Hall measurements of one and the same DW, by determining the impact of super-bandgap illumination on the 2D charge carrier density $n_{2D}$

Toward the reproducible fabrication of conductive ferroelectric domain walls into lithium niobate bulk single crystals

Ferroelectric domain walls (DWs) are promising structures for assembling future nano-electronic circuit elements on a larger scale since reporting domain wall currents of up to 1 mA per single DW. One key requirement hereto is their reproducible manufacturing by gaining preparative control over domain size and domain wall conductivity (DWC). To date, most works on DWC have focused on exploring the fundamental electrical properties of individual DWs within single-shot experiments, with an emphasis on quantifying the origins of DWC. Very few reports exist when it comes to comparing the DWC properties between two separate DWs, and literally nothing exists where issues of reproducibility in DWC devices have been addressed. To fill this gap while facing the challenge of finding guidelines for achieving predictable DWC performance, we report on a procedure that allows us to reproducibly prepare single hexagonal domains of a predefined diameter into uniaxial ferroelectric lithium niobate single crystals of 200 and 300  m thickness, respectively. We show that the domain diameter can be controlled with an uncertainty of a few percent. As-grown DWs are then subjected to a standard procedure of current-limited high-voltage DWC enhancement, and they repetitively reach a DWC increase of six orders of magnitude. While all resulting DWs show significantly enhanced DWC values, their individual current–voltage (I–V) characteristics exhibit different shapes, which can be explained by variations in their 3D real structure reflecting local heterogeneities by defects, DW pinning, and surface-near DW inclination

Анализ осветительной установки центра спортивной подготовки "Заря"

In the work provided an analysis of the lighting system UIA Sports Training Centre "Dawn", Novosibirsk and calculation of payback lighting installation when replacing an existing system on led light sources

Subjective cognitive complaints and blood biomarkers of neurodegenerative diseases: a longitudinal cohort study

Background Subjective cognitive complaints (SCC) have been mostly studied in the context of Alzheimer’s disease in memory clinic settings. The potential of combining SCC with genetic information and blood biomarkers of neurodegenerative diseases for risk assessment of dementia and depression in the absence of dementia among community-dwelling older adults has so far not been explored. Methods Data were based on a population-based cohort of 6357 participants with a 17-year follow-up (ESTHER study) and a clinic-based cohort of 422 patients. Participants of both cohorts were grouped according to the diagnosis of dementia (yes/no) and the diagnosis of depression in the absence of dementia (yes/no). Participants without dementia included both cognitively unimpaired participants and cognitively impaired participants. Genetic information (APOE ε4 genotype) and blood-based biomarkers of neurodegenerative diseases (glial fibrillary acidic protein; GFAP, neurofilament light chain; NfL, phosphorylated tau181; p-tau181) were available in the ESTHER study and were determined with Simoa Technology in a nested case–control design. Logistic regression models adjusted for relevant confounders were run for the outcomes of all-cause dementia and depression in the absence of dementia. Results The results showed that persistent SCC were associated both with increased risk of all-cause dementia and of depression without dementia, independently of the diagnostic setting. However, the results for the ESTHER study also showed that the combination of subjective complaints with APOE ε4 and with increased GFAP concentrations in the blood yielded a substantially increased risk of all-cause dementia (OR 5.35; 95%CI 3.25–8.81, p-value < 0.0001 and OR 7.52; 95%CI 2.79–20.29, p-value < 0.0001, respectively) but not of depression. Associations of NfL and p-tau181 with risk of all-cause dementia and depression were not statistically significant, either alone or in combination with SCC, but increased concentrations of p-tau181 seemed to be associated with an increased risk for depression. Conclusion In community and clinical settings, SCC predict both dementia and depression in the absence of dementia. The addition of GFAP could differentiate between the risk of all-cause dementia and the risk of depression among individuals without dementia

Structural analysis of the Ss sialoglycoprotein specific for Henshaw blood group from human erythrocyte membranes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66122/1/j.1432-1033.1984.tb08155.x.pd