Zonguldak Karaelmas University

About: Zonguldak Karaelmas University is a based out in . It is known for research contribution in the topics: Population & Copolymer. The organization has 1939 authors who have published 4296 publications receiving 62466 citations.

Stochastic resonance in hybrid scale-free neuronal networks

Abstract: We study the phenomenon of stochastic resonance in a system of coupled neurons that are globally excited by a weak periodic input signal. We make the realistic assumption that the chemical and electrical synapses interact in the same neuronal network, hence constituting a hybrid network. By considering a hybrid coupling scheme embedded in the scale-free topology, we show that the electrical synapses are more efficient than chemical synapses in promoting the best correlation between the weak input signal and the response of the system. We also demonstrate that the average degree of neurons within the hybrid scale-free network significantly influences the optimal amount of noise for the occurrence of stochastic resonance, indicating that there also exists an optimal topology for the amplification of the response to the weak input signal. Lastly, we verify that the presented results are robust to variations of the system size.

Land cover mapping using sentinel-1 sar data

Abstract: . In this paper, the potential of using free-of-charge Sentinel-1 Synthetic Aperture Radar (SAR) imagery for land cover mapping in urban areas is investigated. To this aim, we use dual-pol (VV+VH) Interferometric Wide swath mode (IW) data collected on September 16th 2015 along descending orbit over Istanbul megacity, Turkey. Data have been calibrated, terrain corrected, and filtered by a 5x5 kernel using gamma map approach. During terrain correction by using a 25m resolution SRTM DEM, SAR data has been resampled resulting into a pixel spacing of 20m. Support Vector Machines (SVM) method has been implemented as a supervised pixel based image classification to classify the dataset. During the classification, different scenarios have been applied to find out the performance of Sentinel-1 data. The training and test data have been collected from high resolution image of Google Earth. Different combinations of VV and VH polarizations have been analysed and the resulting classified images have been assessed using overall classification accuracy and Kappa coefficient. Results demonstrate that, combining opportunely dual polarization data, the overall accuracy increases up to 93.28% against 73.85% and 70.74% of using individual polarization VV and VH, respectively. Our preliminary analysis points out that dual polarimetric Sentinel-1SAR data can be effectively exploited for producing accurate land cover maps, with relevant advantages for urban planning and management of large cities.

Recognition Model for Solar Radiation Time Series based on Random Forest with Feature Selection Approach

Abstract: Solar photovoltaic (PV) energy, one of fast growing energy technologies in the world, provides cheap opportunities for future energy generation. Solar radiation estimation models play an important role in efficient utilization of solar PV energy. In this paper, we propose a high performance recognition model for solar radiation based on random forest (RF) with feature selection approach to cope with nonlinear dynamics in time series. Forty-five features have been extracted from the temperature, pressure, wind speed and humidity data as well as solar radiation data using the moving average indicator. In addition, the total of 50 features has been extracted together with the five features obtained based on the previous values of the five parameters specified. The features that will improve model performance have been determined by the forward selection approach and the model, which has the highest performance, has been proposed for solar radiation estimation.

Autaptic pacemaker mediated propagation of weak rhythmic activity across small-world neuronal networks

Abstract: We study the effects of an autapse, which is mathematically described as a self-feedback loop, on the propagation of weak, localized pacemaker activity across a Newman–Watts small-world network consisting of stochastic Hodgkin–Huxley neurons. We consider that only the pacemaker neuron, which is stimulated by a subthreshold periodic signal, has an electrical autapse that is characterized by a coupling strength and a delay time. We focus on the impact of the coupling strength, the network structure, the properties of the weak periodic stimulus, and the properties of the autapse on the transmission of localized pacemaker activity. Obtained results indicate the existence of optimal channel noise intensity for the propagation of the localized rhythm. Under optimal conditions, the autapse can significantly improve the propagation of pacemaker activity, but only for a specific range of the autaptic coupling strength. Moreover, the autaptic delay time has to be equal to the intrinsic oscillation period of the Hodgkin–Huxley neuron or its integer multiples. We analyze the inter-spike interval histogram and show that the autapse enhances or suppresses the propagation of the localized rhythm by increasing or decreasing the phase locking between the spiking of the pacemaker neuron and the weak periodic signal. In particular, when the autaptic delay time is equal to the intrinsic period of oscillations an optimal phase locking takes place, resulting in a dominant time scale of the spiking activity. We also investigate the effects of the network structure and the coupling strength on the propagation of pacemaker activity. We find that there exist an optimal coupling strength and an optimal network structure that together warrant an optimal propagation of the localized rhythm.

Neuroprotective effects of Nigella sativa on experimental spinal cord injury in rats

Abstract: The aim of this study was to investigate the possible beneficial effects of Nigella sativa (NS) in comparison to methylprednisolone on experimental spinal cord injury (SCI) in rats. SCI was performed by placing an aneurysm clip extradurally at the level of T11-12. Rats were neurologically tested over 24 h after trauma and spinal cord tissue samples were harvested for both biochemical and histopathological evaluation. The neurological scores of rats were not found to be different in SCI groups. SCI significantly increased the spinal cord tissue malondialdehyde (MDA) and protein carbonyl (PC) levels, however SCI decreased superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) enzyme activities compared to the control. Methylprednisolone and NS treatment decreased tissue MDA and PC levels and prevented inhibition of SOD, GSH-Px and CAT enzymes in the tissues. The most significant results were obtained when NS was given. In SCI and placebo groups, the neurons of spinal cord tissue became extensively dark and degenerated with picnotic nuclei. The morphology of neurons in methylprednisolone and NS-treated groups were well protected, however, not as well as the neurons of the control group. The number of neurons in the spinal cord tissue of the SCI and placebo groups was significantly less than the control, laminectomy, methylprednisolone and NS-treated groups. In conclusion, NS treatment might be beneficial in spinal cord tissue damage, and therefore shows potential for clinical implications.