''On February 6th, 2023, two severe earthquakes struck southeastern Türkiye near the Syrian border. The first earthquake, Mw7.8, occurred at 04:17 local time in the East Anatolian Fault Zone near the city of Gaziantep. The second earthquake, Mw7.5, occurred approximately 9 h later at 13:24 local time near Elbistan County, in Kahramanmaraş province. These seismic events ruptured multiple segments of the East Anatolian Fault Zone (EAFZ), with rupture lengths exceeding 300 km, and deformation exceeding 5 m on both sides of the faults. In this study, we aim to analyze characteristics of the strong ground motion induced by the mainshocks, focusing on ground motion intensity measures such as the peak ground acceleration (PGA), the peak ground velocity (PGV), and the pseudo-acceleration response spectra (PSA). The first earthquake produced extremely high PGA values in both horizontal (> 2 g) and vertical (> 1 g) components. At near field distances, large PGVs are measured (> 180 cm/s) with more than 30 impulsive motions which may indicate source-related effects. Large spectral demands are also recorded for both earthquakes, partially underestimated by Ground Motion Models (GMMs), especially in the near-field. Specifically, we compare the PSA for horizontal directions with the design spectra provided by both the new and previous Turkish building codes. We also present building and ground damage observations that provide insights into the observed ground motions in the heavily damaged areas.''
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Precast concrete structures are preferred for facilities with large open areas due to easiness in construction. Such structures are typically composed of individual columns and long-span beams, and are quite flexible and of limited redundancy. In this paper, nonlinear dynamic analyses of a typical such structure are conducted using as excitation 54 ground motions recorded on top of a variety of soils (hard, soft, and liquefied soil sites). The results show that liquefaction-affected level-ground motions systematically impose a greater threat to precast-concrete structures in terms of seismic demand, even when low values of elastic spectral acceleration prevail, as opposed to soft-soil records and even more to hard-soil ones. Thus, elastic spectral acceleration appears to be an insufficient engineering demand parameter for design. Soil effects, the “signature” of which is born on ground motions, are first uncovered using wavelet analysis to detect the evolution of the energy and frequency content of the ground motion in the time domain. From this, the changes in effective (“dominant”) excitation period are noted, persuasively attributed to the nature of the soil, and finally correlated with the observed structural behavior.
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A damage estimation exercise has been carried out using the building stock inventory and population database of the Istanbul Metropolitan Municipality and selected European earthquake loss estimation packages: KOERILOSS, SELENA, ESCENARIS, SIGE, and DBELA. The input ground-motions, common to all models, correspond to a “credible worst case scenario” involving the rupture of the four segments of the Main Marmara Fault closest to Istanbul in a Mw 7.5 earthquake. The aim of the exercise is to assess the applicability of the selected software packages to earthquake loss estimation in the context of rapid post-earthquake response in European urban centers. The results in terms of predicted building damage and social losses are critically compared amongst each other, as well as with the results of previous scenario-based earthquake loss assessments carried out for the study area. The key methodological aspects and data needs for European rapid post-earthquake loss estimation are thus identified.
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In sports, inertial measurement units are often used to measure the orientation of human body segments. A Madgwick (MW) filter can be used to obtain accurate inertial measurement unit (IMU) orientation estimates. This filter combines two different orientation estimates by applying a correction of the (1) gyroscope-based estimate in the direction of the (2) earth frame-based estimate. However, in sports situations that are characterized by relatively large linear accelerations and/or close magnetic sources, such as wheelchair sports, obtaining accurate IMU orientation estimates is challenging. In these situations, applying the MW filter in the regular way, i.e., with the same magnitude of correction at all time frames, may lead to estimation errors. Therefore, in this study, the MW filter was extended with machine learning to distinguish instances in which a small correction magnitude is beneficial from instances in which a large correction magnitude is beneficial, to eventually arrive at accurate body segment orientations in IMU-challenging sports situations. A machine learning algorithm was trained to make this distinction based on raw IMU data. Experiments on wheelchair sports were performed to assess the validity of the extended MW filter, and to compare the extended MW filter with the original MW filter based on comparisons with a motion capture-based reference system. Results indicate that the extended MW filter performs better than the original MW filter in assessing instantaneous trunk inclination (7.6 vs. 11.7◦ root-mean-squared error, RMSE), especially during the dynamic, IMU-challenging situations with moving athlete and wheelchair. Improvements of up to 45% RMSE were obtained for the extended MW filter compared with the original MW filter. To conclude, the machine learning-based extended MW filter has an acceptable accuracy and performs better than the original MW filter for the assessment of body segment orientation in IMU-challenging sports situations.
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Accurate assessment of rolling resistance is important for wheelchair propulsion analyses. However, the commonly used drag and deceleration tests are reported to underestimate rolling resistance up to 6% due to the (neglected) influence of trunk motion. The first aim of this study was to investigate the accuracy of using trunk and wheelchair kinematics to predict the intra-cyclical load distribution, more particularly front wheel loading, during hand-rim wheelchair propulsion. Secondly, the study compared the accuracy of rolling resistance determined from the predicted load distribution with the accuracy of drag test-based rolling resistance. Twenty-five able-bodied participants performed hand-rim wheelchair propulsion on a large motor-driven treadmill. During the treadmill sessions, front wheel load was assessed with load pins to determine the load distribution between the front and rear wheels. Accordingly, a machine learning model was trained to predict front wheel load from kinematic data. Based on two inertial sensors (attached to the trunk and wheelchair) and the machine learning model, front wheel load was predicted with a mean absolute error (MAE) of 3.8% (or 1.8 kg). Rolling resistance determined from the predicted load distribution (MAE: 0.9%, mean error (ME): 0.1%) was more accurate than drag test-based rolling resistance (MAE: 2.5%, ME: −1.3%).
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Blended learning is not a flash in the pan, it’s here to stay. At The Hague University of Applied Sciences (THUAS) the implementation of blended learning is not yet in an adult stage, but in a newly introduced educational framework (The Hague University of Applied Sciences, 2017) blended learning plays a vital role. The intention is for teams to come to a shared approach when it comes to blended learning. In his blog, Leonard Geluk, (Geluk, 2016) the Chairman of the Executive Board of the University notes that ‘the development is slow to get off the ground’ and ‘there is still work to be done before we can fully embed ICT in education.’ The toolkit of teachers has been supplemented with many digital tools in recent decades (Geluk, 2014), but what makes lecturers actually use these new possibilities? What causes them to pick up the toolkit or leave it? Jacobs (2013) indicates that people’s ability to exploit the benefits of technology, in particular digital technology, is not obvious and can be a big challenge, especially for teachers. The central question to this study is: What brings lecturers in motion around blended learning? In my opinion, gaining more understanding in the lecturers’ perspective is an important part of the ‘work’ that Leonard Geluk describes above. This is the main goal of this research.
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Introduction: Falling causes long term disability and can even lead to death. Most falls occur during gait. Therefore improving gait stability might be beneficial for people at risk of falling. Recently arm swing has been shown to influence gait stability. However at present it remains unknown which mode of arm swing creates the most stable gait. Aim: To examine how different modes of arm swing affect gait stability. Method: Ten healthy young male subjects volunteered for this study. All subjects walked with four different arm swing instructions at seven different gait speeds. The Xsens motion capture suit was used to capture gait kinematics. Basic gait parameters, variability and stability measures were calculated. Results: We found an increased stability in the medio-lateral direction with excessive arm swing in comparison to normal arm swing at all gait speeds. Moreover, excessive arm swing increased stability in the anterior–posterior and vertical direction at low gait speeds. Ipsilateral and inphase arm swing did not differ compared to a normal arm swing. Discussion: Excessive arm swing is a promising gait manipulation to improve local dynamic stability. For excessive arm swing in the ML direction there appears to be converging evidence. The effect of excessive arm swing on more clinically relevant groups like the more fall prone elderly or stroke survivors is worth further investigating. Conclusion: Excessive arm swing significantly increases local dynamic stability of human gait.
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By supporting creation of protected areas, conservation projects are known to bring economic prosperity to the local communities, but also incite criticism. A common theme in the critique of conservation organizations is the proximity to neoliberal agencies seeking to capitalize on environment, which disadvantage the local communities. Community participation has been proposed as a panacea for neoliberal conservation. However, conservation efficacy is not always contingent on the community involvement and reliance on ‘traditional’ practices in protected areas has not always benefitted biodiversity. Simultaneously, critique of conservation ignores evidence of indigenous activism as well as alternative forms of environmentalism which provide a broader ethical support base for conservation. This article highlights the challenges and contradictions, as well as offers hopeful directions in order to more effectively ground compassionate conservation. https://doi.org/10.1080/23251042.2015.1048765 https://www.linkedin.com/in/helenkopnina/
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Exposure data available to developers of earthquake loss models are often very crudely aggregated spatially, and in such cases very considerable effort can be required to refine the geographical resolution of the building stock inventory. The influence of the geographical resolution of the exposure data for the Sea of Marmara region in Turkey is explored using several different levels of spatial aggregation to estimate the losses due to a single earthquake scenario. The results show that the total damage over an urban area, expressed as a mean damage ratio (MDR), is rather insensitive to the spatial resolution of the exposure data if a sufficiently large number of ground-motion simulations are used. However, the variability of the MDR estimates does reduce as the spatial resolution becomes higher, reducing the number of simulations required, although there appears to be a law of diminishing returns in going to very high exposure data resolution. This is largely due to the inherent and irreducible spatial variability of ground motion, which suggests that if only mean MDR estimates are needed, the effort required to refine the spatial definition of exposure data is not justified.
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