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Synthesis and characterization of ozonated oil nanoemulsions

Tığlı-Aydın, Rahime Seda | Kazancı, Füsun

Article | 2018 | JAOCS, Journal of the American Oil Chemists' Society95 ( 11 ) , pp.1385 - 1398

In recent years, the use of ozonated oil (ozone enriched oil form) is being increasingly preferred for biomedical applications because of its antibacterial activity. Among most important reasons of this choice is the high molecular affinity of the ozone molecule and intracellular effects of the products of ozone and the unsaturated fatty-acid chemical reactions in cellular signaling systems. The aim of the present study was to synthesize and optimize the ozonated oil nanoemulsion system that would be transferred into the living systems easily, suggesting a promising carrier system for various biomedical applications. By varying form . . .ulation parameters (surfactant-to-oil ratio, surfactant concentration, mixing rate, and surfactant type), nanoemulsions were investigated in terms of mean particle diameters, distributions, and stabilities. Nanoemulsions with high stability and small droplet diameters (212.7 nm) could be produced under optimized conditions with Tween 40 as the surfactant at a 750 rpm mixing rate using the emulsion inversion point (EIP) low-energy method. Spherical and uniformly distributed nanoemulsions were observed by SEM, which also supports mean particle diameter measurements. Fourier-transform infrared spectroscopy (FTIR) and 13C NMR (nuclear magnetic resonance) studies indicated an ozonide structure within the nanoemulsion system, which remained even after 30 days of storage. The antibacterial activity of ozonated oil emulsions against Staphylococcus aureus and Escherichia coli suggests promising applications in the biomedical field. © 2018 AOC Daha fazlası Daha az

Effect of channel noise and dynamic synapse structure on latency dynamics in neural system

Çalım, Ali | Özer, Mahmut | Uzuntarla, Muhammet

Proceedings | 2018 | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp.1 - 4

Experimental and theoretical studies in recent years suggest that the first spike latency is an effective information carrier and contains more neural information than other spikes. Noise Delayed Decay (NDD) phenomenon emerges when the first spike latency of the neuron exposed to the periodic driving is maximum at a certain noise intensity interval. In this study, the latency dynamics of a single Hodgkin-Huxley neuron is investigated under periodic driving, background activity through dynamic synapses, and channel noise. The system response with first spike latency is investigated as a function of the presynaptic firing rate, the pa . . .rameter with an appropriate biophysical reality to control the level of activity in the nervous system. First, NDD behavior is investigated under suprathreshold stimulation in the presence of synapses at different levels of depression and channel noise. It is then desired to observe the NDD phenomenon under subthreshold stimulation with the same strategy. Our results have shown that the background activity occurring in the presence of dynamic synapses and the channel noise are significant system dynamics in observing the NDD behavior. © 2018 IEEE Daha fazlası Daha az

Classification of refractive disorders from electrooculogram (EOG) signals by using data mining techniques

Kaya, Ceren | Erkaymaz, Okan | Ayar, Orhan | Özer, Mahmut

Proceedings | 2018 | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp.1 - 4

Refractive disorders are common health problems in the community and they are the most important cause of visual impairment. In this study, it was aimed to classify the individuals who have hypermetropia and myopia refractive disorders or not. For this, horizontal and vertical Electrooculogram (EOG) signal data from the right and left eyes of the individuals were used. The performance of the data was investigated by using Logistic Regression (LR), Naive Bayes (NB), Random Forest (RF) and REP Tree (RT) data mining methods. According to the obtained results, REP Tree method has shown the most successful classification performance to d . . .etect hypermetropia and myopia refractive disorders from Electrooculogram (EOG) signals. © 2018 IEEE Daha fazlası Daha az

Effects of calcium channel noise on weak signal detection in neuron-astrocyte interactions

Erkan, Yasemin | Saraç, Zehra | Yılmaz, Ergin

Proceedings | 2018 | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp.1 - 4

In this study, the effects of electrically non-excitable astrocyte cell on the weak signal detection capacity of Hodgkin-Huxley neuron are investigated. To do this, by applying a subthreshold weak signal to neuron, we investigate the weak signal detection capacity of the neuron depending on calcium channel noise stemmed from random open-close fluctuations of calcium channels. Obtained results show that astrocyte decreases the weak signal detection capacity of Hodgkin-Huxley neuron. © 2018 IEEE.

Classification of cervical cancer data and the effect of random subspace algorithms on classification performance

Erkaymaz, Okan | Palabaş, Tuğba

Proceedings | 2018 | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp.1 - 4

Computer assisted automatic diagnostic systems are used for the purpose of speeding up diagnosis and treatment and helping to make the right decision. In this study, cervical cancer is identified using four basic classifiers: Naive Bayes (NB), k-Nearest Neighbor (kNN), Multilayer Perceptron (MLP) and Decision Trees (KA-C4.5) algorithms and random subspaces ensemble algorithm. Gain Ratio Attribute Evaluation (GRAE) feature extraction algorithm is applied to contribute to classification performance. The classification results obtained with all datasets and reduced datasets are compared with respect to performance criteria such as accu . . .racy, Root Mean Square Error (RMSE), Sensitivity, Specificity performance criteria. According to the obtained performance analysis, it is seen that the classification performance with the random subspace ensemble algorithm using the kNN basic classifier on the reduced data set is the highest (%95.51). © 2018 IEEE Daha fazlası Daha az

Effects of autapse on weak signal detection in FFL network motifs

Baysal, Veli | Yılmaz, Ergin

Proceedings | 2018 | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp.1 - 4

In this paper, effects of autapse on signal detection capacity of Izhikevich neuron in feed-forward-loop network motifs are investigated. Obtained results showed that autapse significantly enchances singal detection of Izhikevich neuron at proper autaptic time delay values compared without autapse. Also, it is seen that feed-forward-loop motifs have significant effects on signal detection ability of Izhikevich neuron. It is obtained that signal detection of Izhikevich neuron are best in T1 feed-forward-loop motif. © 2018 IEEE.

Chimera states in networks of type-I Morris-Lecar neurons

Çalım, Ali | Hövel, Philipp | Özer, Mahmut | Uzuntarla, Muhammet

Article | 2018 | Physical Review E98 ( 6 ) , pp.1 - 4

Chimeras are complex spatiotemporal patterns that emerge as coexistence of both coherent and incoherent groups of coupled dynamical systems. Here, we investigate the emergence of chimera states in nonlocal networks of type-I Morris-Lecar neurons coupled via chemical synapses. This constitutes a more realistic neuronal modeling framework than previous studies of chimera states, since the Morris-Lecar model provides biophysically more relevant control parameters to describe the activity in actual neural systems. We explore systematically the transitions of dynamic behavior and find that different types of synchrony appear depending on . . . the excitability level and nonlocal network features. Furthermore, we map the transitions between incoherent states, traveling waves, chimeras, coherent states, and global amplitude death in the parameter space of interest. This work contributes to a better understanding of biological conditions giving rise to the emergence of chimera states in neural medium. © 2018 American Physical Society Daha fazlası Daha az

Subthreshold signal detection in heterogeneous neural networks

Çalım, Ali | Özer, Mahmut | Uzuntarla, Muhammet

Proceedings | 2018 | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp.1 - 4

In this study, effects of the heterogeneity in neuronal networks and subthreshold signal features on subthreshold signal detection in the nervous system is investigated. As most of studies in the literature investigate the subject by considering neuron populations as homogenous systems, in this study, the populations are considered as heterogeneous in terms of neuronal excitability. The information processing performance of the neuron populations is systematically studied by using mathematical equations for modeling the dynamics of the neurons, which are basic units of the system. As a result of the simulations performed, it is seen . . . that the sub-threshold signal frequency and the heterogeneity in the excitability are important system parameters for optimizing the information encoding performance. It is shown that the population encoding performance is maximized depending on the subthreshold signal frequency at different optimum levels of heterogeneity in the population. © 2018 IEEE Daha fazlası Daha az

Impact of hybrid neural network on the early diagnosis of diabetic retinopathy disease from video-oculography signals

Kaya, Ceren | Erkaymaz, Okan | Ayar, Orhan | Özer, Mahmut

Article | 2018 | Chaos, Solitons and Fractals114 , pp.164 - 174

In this study, we introduce two hybrid artificial neural network models with particle swarm optimization algorithm to diagnose diabetic retinopathy based on the Video-Oculography signals. The hybrid models use Discrete Wavelet Transform and Hilbert-Huang Transform separately to extract features from the signals. The classification performance of both models is analyzed comparatively. We show that the model based on Hilbert–Huang Transform exhibits better classification performance than the model based on the Discrete Wavelet Transform. © 2018 Elsevier Ltd

Vibrational resonance in a Hodgkin-Huxley neuron under electromagnetic induction

Baysal, Veli | Yılmaz, Ergin

Proceedings | 2018 | 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp.1 - 4

In this paper, effects of electromagnetic induction on vibrational resonance phenomenon in a Hodgkin-Huxley neuron are investigated. By stimulating Hodgkin-Huxley neuron with both high-frequency signal and low-frequency weak signal, its weak signal detection capacity have been investigated under electromagnetic induction effect. Obtained results show that electromagnetic induction causes decreasing of the amplitude of vibrational resonance effect emerging depending on the amplitude of high frequency signal. Also, vibrational resonance phenomenon occurs at smaller amplitudes of high frequency signal in Hodgkin-Huxley neuron which is . . .under electromagnetic induction effect. Finally, it is found that the best detection of the weak signal in a Hodgkin-Huxley neuron under electromagnetic induction effect is realized under an optimal electromagnetic current intensity. © 2018 IEEE Daha fazlası Daha az

Soybean oil based polylactic acid membranes: Synthesis and degradation characteristics

Aydın Tığlı, R. Seda | Akyol, Elvan | Hazer, Baki

Article | 2018 | Journal of Polymers and the Environment26 ( 3 ) , pp.1262 - 1271

Controlling the degradation parameters is one of the main challenges of preparing appropriate biomaterials for biomedical applications. In this study, the effect of soybean oil inclusion on hydrolytic degradation of polylactic acid (PLA) was investigated both in vitro and in vivo. PLA/oil membranes were prepared by using polymeric soybean oil (PSO), epoxidized soybean oil and soybean oil (SOYA) with their varied concentrations. Degradation of membranes was performed in vitro for 8 weeks period and in vivo for 4 weeks period. Weight loss, changes in molecular weight, thermal properties and morphological changes were studied during de . . .gradation. SOYA blended PLA membranes show the lowest degradation rates by bulk degradation after 4 weeks in vitro, followed by surface erosion for the first week. Approximately twofold high percentage weight losses of all membranes were obtained after 4 weeks of degradation in vivo in comparison with in vitro data. The significant weight loss, molecular weight loss and thermal property change for PSO blended membranes were determined during in vivo degradation which highlights the increase of degradation rate by bulk degradation. Drastic morphological changes were observed on surface of degraded membranes in vivo with large pores, cracks, fissures and large cavities. © 2017, Springer Science+Business Media New York Daha fazlası Daha az

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