6 research outputs found

    Automated detection of discontinuities in EUREF permanent GNSS network stations due to earthquake events

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    [EN] The EUREF Permanent GNSS Network (EPN) provides the users with data and products such as station coordinate time series. These are subject to possible discontinuities and trend changes, being earthquake events one of the possible natural causes for these variations. We present here a fully automated tool for the analysis of the coordinate time series of EPN stations located in the desired neighbourhood of an earthquake epicentre. The tool is made freely available to the public and applied here to two significant earthquake events occurred in Europe in recent years, where several trend changes and jumps are revealed.Baselga Moreno, S.; Najder, J. (2022). Automated detection of discontinuities in EUREF permanent GNSS network stations due to earthquake events. Survey Review. 54(386):420-428. https://doi.org/10.1080/00396265.2021.19642304204285438

    Theory of Punctuated Equilibrium - Central Assumptions and Concepts

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    Artykuł przedstawia podstawy teorii przerywanej równowagi sformułowanej jako alternatywne względem gradualistycznego darwinizmu ujęcie przebiegu makroewolucji. Twórcami teorii przerywanej równowagi są amerykańscy paleontologowie Stephen Jay Gould i Niles Eldredge, według których proces makroewolucji nie zachodzi stopniowo, małymi kroczkami, lecz charakteryzuje się długimi okresami stazy, które co jakiś czas przerywane są szybkimi - w skali geologicznej - przemianami organizmów.The article presents foundations of the theory of punctuated equilibrium which was formulated as an alternative account of the course of macroevolution to gradualistic Darwinism. Founders of the theory of punctuated equilibrium are American paleontologists Stephen Jay Gould and Niles Eldredge who claim that the process of macroevolution does not occur gradually, step by step, but it is characterized by long periods of stasis punctuated, from time to time, by rapid – on geological scale – transformations of organisms

    Quality of Orbit Predictions for Satellites Tracked by SLR Stations

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    This study aims to evaluate and analyze the orbit predictions of selected satellites: geodetic, Global Navigational Satellite Systems (GNSS), and scientific low-orbiting, which are tracked by laser stations. The possibility of conducting satellite laser ranging (SLR) to artificial satellites depends on the access to high-quality predictions of satellite orbits. The predictions provide information to laser stations where to aim the telescope in search of a satellite to get the returns from the retroreflectors installed onboard. If the orbit predictions are very imprecise, SLR stations must spend more time to correct the telescope pointing, and thus the number of collected observations is small or, in an extreme case, there are none of them at all. Currently, there are about 120 satellites equipped with laser retroreflectors orbiting the Earth. Therefore, the necessity to determine the quality of predictions provided by various analysis centers is important in the context of the increasing number of satellites tracked by SLR stations. We compare the orbit predictions to final GNSS orbits, precise orbits of geodetic satellites based on SLR measurements determined in postprocessing, and kinematic orbits of low-orbiting satellites based on GPS data. We assess the quality degradation of the orbit predictions over time depending on the type of orbit and the satellite being analyzed. We estimate the time of usefulness of prediction files, and indicate those centers which publish most accurate predictions of the satellites’ trajectories. The best-quality predictions for geodetic satellites and Galileo reach the mean error of 0.5–1 m for the whole 5-day prediction file (for all three components), while the worst ones can reach values of up to several thousand meters during the first day of the prediction

    The relationship between psychosocial risks and occupational functioning among miners

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    Objectives This paper presents the results of research on the scale of psychosocial risks among miners. A comparative analysis was made, comparing the research results with the data obtained from workers in the following industries: metal, energy, chemical and construction – along with an indication of the relationship between stressful working conditions and the occupational functioning of the respondents. Material and Methods The study involved 483 adults employed in mines in Poland. The study on psychosocial risks in the workplace was performed using Psychosocial Risk Scale , developed by the Department of Health and Work Psychology of the Nofer Institute of Occupational Medicine, Łódź, Poland. Psychosocial Risk Scale is the scientifically validated diagnostic tool and is characterized by high reliability and validity of coefficients. Results The analysis of differences in occupational functioning between miners and other workers in heavy industry provides that miners are in general more healthy, less stressed, more positive emotionally and normatively committed to work, more satisfied with work, and more stable in the employment (as opposite to turnover intention) than the other workers. The results suggest that miners with a lower level of stress functioned at work better – they evaluated their health and ability to work better than miners with a higher level of stress. Their intention to change a job was lower than among those experiencing more stress. The most pronounced effect was observed for the influence on this dimension of functioning by job context risks (the higher level of probability, and the higher t-test value). Conclusions Occupational functioning of miners in Poland is better than the other employees in heavy industry. The analysis of differences in occupational functioning dimensions provides that a lower level of psychosocial risk in a workplace is connected with a higher level of job satisfaction, positive affective and normative work commitment and a lower level of turnover intension. Int J Occup Med Environ Health. 2019;32(1):87–9
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