Photometry of three chromospherically active stars: V340 Gem,SAO 62042 and FI Cnc

We present a photometric study of three chromospherically active stars with long periods (V340 Gem, SAO 62042 and FI Cnc). The observations were made at the ÇOMU Observatory in 2006 and 2007. We have made initial photometric analyses of V340 Gem and SAO 62042, which are newly discovered RS CVn–type SB1 binaries, and established the photometric variations of FI Cnc, which is a single G8III active star. Photometric rotation periods of these stars were obtained by analyzing their light variations. The light variations, observed over three or more consecutive orbital cycles, were investigated by using spot models with the program SPOT. We also discussed the surface differential rotation coefficient for the primary component of the SB1 binary star SAO 62042 in this study, using our own photometric period together with an orbital period taken from the literature.     

Evaluating of the earthquake hazard parameters with Bayesian method for the different seismic source regions of the North Anatolian Fault Zone

The earthquake hazard parameters and earthquake occurrence probabilities are computed for the different regions of the North Anatolia Fault Zone (NAFZ) using Bayesian method. A homogenous earthquake catalog for M _S magnitude which is equal or larger than 4.0 is used for a time period between 1900 and 2015. Only two historical earthquakes (1766, M _S = 7. 3 and 1897, M _S = 7. 0) are included in Region 2 (Marmara Region) where a large earthquake is expected in the near future since no large earthquake has been observed for the instrumental period. In order to evaluate earthquake hazard parameters for next 5, 10, 20, 50, 100 years, M _max (maximum regional magnitude), β value, λ (seismic activity or density) are computed for the different regions of NAFZ. The computed M _max values are changed between 7.11 and 7.89. While the highest magnitude value is calculated in the Region 9 related to Tokat-Erzincan, the lowest value in the Region 10 including the eastern of Erzincan. The “quantiles” of “apparent” and “true” magnitudes of future time intervals of 5, 10, 20, 50, and 100 years are calculated for confidence limits of probability levels of 50, 70 and 90 % of the 10 different seismic source regions. The region between Tokat and Erzincan has earthquake hazard level according to the determined parameters. In this region the expected maximum earthquake size is 7.8 with 90 % occurrence probability in next 100 years. While the regional M _max value of Marmara Region is computed as 7.61, expected maximum earthquake size is 7.37 with 90 % occurrence probability in next 100 years.     

Magnetotelluric images of the crust and mantle in the southwestern Taurides, Turkey

Inversion of the magnetotelluric data across the southwestern Taurides reveals two subzones of crust with varying thicknesses: conductive lower crust (<75 Ω m), overlain by resistive (>350 Ω m) upper crust, with four resistive cores (>2000 Ω m) separated by three relatively conductive vertical zones. The first and second vertical zones coincide with surface faults interpreted in Anatolia, such as Fethiye Burdur Fault Zone. The third one is the most conductive and lies in continuity with the Strabo Fault Zone in the Mediterranean Sea. A hypocentral cross section of earthquakes along the profile shows more dense seismic activity in the second resistive core where the conductive crust is not present beneath it. The depth of the crust/upper mantle boundary varies between 30 and 50 km and has an undulating character. The resistivity of the upper mantle reaches 500–1000 Ω m.     

Dissolution kinetics of natural magnesite in lactic acid solutions

In this study, the dissolution of magnesite particles in aqueous lactic acid solutions was investigated in a batch reactor employing the parameters of stirring speed, particle size, temperature and acid concentration. The shrinking core model was evaluated to determine the effect of particle size, temperature and concentration. It was also found that the stirring speed did not change the dissolution. Consequently, it was determined that the dissolution rate is controlled by surface chemical reaction. The activation energy of the process was determined to be 50.3 kJ mol^− 1.     

Structural and geotechnical investigations on Sivrice earthquake (Mw = 6.8), January 24, 2020

Natural Hazards - The earthquake in Sivrice, the district of Elaz??, took place at 20:55 (with local time, GMT+3) on January 24, 2020, with a magnitude of 6.8 in Turkey. This earthquake...     

Properties of the Aftershock Sequences of the 2003 Bingöl, M D = 6.4, (Turkey) Earthquake

Aftershock sequences of the magnitude M _{W =}6.4 Bingöl earthquake of 1 May, 2003 (Turkey) are studied to analyze the spatial and temporal variability of seismicity parameters of the b value of the frequency-magnitude distribution and the p value describing the temporal decay rate of aftershocks. The catalog taken from the KOERI contains 516 events and one month’s time interval. The b value is found as 1.49 ± 0.07 with Mc =3.2. Considering the error limits, b value is very close to the maximum b value stated in the literature. This larger value may be caused by the paucity of the larger aftershocks with magnitude M _D ≥ 5.0. Also, the aftershock area is divided into four parts in order to detect the differences in b value and the changes illustrate the heterogeneity of the aftershock region. The p value is calculated as 0.86 ± 0.11, relatively small. This small p value may be a result of the slow decay rate of the aftershock activity and the small number of aftershocks. For the fitting of a suitable model and estimation of correct values of decay parameters, the sequence is also modeled as a background seismicty rate model. Constant background activity does not appear to be important during the first month of the Bingöl aftershock sequences and this result is coherent with an average estimation of pre-existing seismicity. The results show that usage of simple modified Omori law is reasonable for the analysis. The spatial variability in b value is between 1.2 and 1.8 and p value varies from 0.6 to 1.2. Although the physical interpretation of the spatial variability of these seismicity parameters is not straightforward, the variation of b and p values can be related to the stress and slip distribution after the mainshock, respectively. The lower b values are observed in the high stress regions and to a certain extent, the largest b values are related to Holocene alluvium. The larger p values are found in some part of the aftershock area although no slip occurred after the main shock and it is interpreted that this situation may be caused by the alluvium structure of the region. These results indicate that the spatial distribution in b and p values are generally related to the rupture mechanism and material properties of an aftershock area.     

Regional Variation of the ω - Upper Bound Magnitude of GIII Distribution in and Around Turkey: Tectonic Implications for Earthquake Hazards

Complete data set of earthquakes in Turkey and the adjacent areas has been used in order to compute the ω values in 24 seismic regions of Turkey. The parameter is obtained through Gumbel’s third asymptotic distribution of extreme values and is well known as upper bound magnitude. This is an interpretation that no earthquake magnitude greater than ω can occur in a region. The results also estimate the most probable magnitude for a time period of 100 years. The estimates of ω exceed the value of 7.00 in 20 of the 24 seismic regions. An effort is also made to find a relation between the magnitude and the length of a fault in the complicated tectonics of Turkey and the surrounding area. Earthquake hazard revealed as tables and maps are also considered for Turkey and the surrounding area.     

Modeling of trophospheric ozone concentrations using genetically trained multi-level cellular neural networks

Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network （ML-CNN） is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications.