Low-dose mirtazapine added to selective serotonin reuptake inhibitors in pregnant women with major depression or panic disorder including symptoms of severe nausea, insomnia and decreased appetite: Three cases
Uguz F.,University of Konya
Journal of Maternal-Fetal and Neonatal Medicine | Year: 2013
Data on the use of a combination of antidepressants during pregnancy are inadequate. This report presents the beneficial effect of low-dose mirtazapine added onto selective serotonin reuptake inhibitors in the treatment of the symptoms of severe nausea, insomnia and loss of appetite accompanying psychiatric disorders during pregnancy, which is an important problem in clinical practice. The psychiatric diagnoses were determined with the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Assessments were performed with the Clinical Global Impression-Improvement Scale and the 17-item Hamilton Rating Scale for Depression. Further studies should be carried out to confirm the positive effects and safety of an additional low-dose mirtazapine in these cases. © 2013 Informa UK Ltd.
Salman M.S.,University of Konya
International Journal of Adaptive Control and Signal Processing | Year: 2014
In this paper, a novel adaptive filter for sparse systems is proposed. The proposed algorithm incorporates a log-sum penalty into the cost function of the standard leaky least mean square (LMS) algorithm, which results in a shrinkage in the update equation. This shrinkage, in turn, enhances the performance of the adaptive filter, especially, when the majority of unknown system coefficients are zero. Convergence analysis of the proposed algorithm is presented, and a stability criterion for the algorithm is derived. This algorithm is given a name of zero-attracting leaky-LMS (ZA-LLMS) algorithm. The performance of the proposed ZA-LLMS algorithm is compared to those of the standard leaky-LMS and ZA-LMS algorithms in sparse system identification settings, and it shows superior performance compared to the aforementioned algorithms. Copyright © 2013 John Wiley & Sons, Ltd.
Torlak E.,University of Konya
International Journal of Food Microbiology | Year: 2014
Alicyclobacillus acidoterrestris survives during the typical pasteurization process and can cause the spoilage of fruit juices thanks to its spore forming and thermo-acidophilic nature. In recent years, A. acidoterrestris has become a major concern to the fruit juices industry worldwide. This study was undertaken to evaluate ozone for the reducing number of A. acidoterrestris spores in apple juice. Apple juice inoculated with A. acidoterrestris spores was bubbled with continuous stream of two different constant concentrations (2.8 and 5.3. mg/L) of ozone at 4 and 22. °C up to 40. min. Level of A. acidoterrestris spores in juice decreased by 2.2 and 2.8 log after 40. min of ozonation at 4. °C with concentrations of 2.8 and 5.3. mg/L, respectively. Treatments at 22. °C for 40. min with 2.8 and 5.3. mg/L ozone resulted in 1.8 and 2.4 log reductions of spore viability, respectively. At the ozone concentration of 5.3. mg/L, significant (P<. 0.05) reductions were observed in total phenolic content of juice at both temperature levels. However, treatments performed at 2.8. mg/L were observed to have no significant (P>. 0.05) effect on total phenolic content. The results presented in this study indicate that over the 2 log reduction in the count of A. acidoterrestris spores in apple juice can be achieved by bubbling ozonation at 4. °C without causing a significant decrease in total phenolic content of product. Therefore, it can be suggested that bubbling ozonation is a promising method for the control of A. acidoterrestris in fruit juices. © 2013 Elsevier B.V.
Uguz H.,University of Konya
Knowledge-Based Systems | Year: 2011
Text categorization is widely used when organizing documents in a digital form. Due to the increasing number of documents in digital form, automated text categorization has become more promising in the last ten years. A major problem of text categorization is its large number of features. Most of those are irrelevant noise that can mislead the classifier. Therefore, feature selection is often used in text categorization to reduce the dimensionality of the feature space and to improve performance. In this study, two-stage feature selection and feature extraction is used to improve the performance of text categorization. In the first stage, each term within the document is ranked depending on their importance for classification using the information gain (IG) method. In the second stage, genetic algorithm (GA) and principal component analysis (PCA) feature selection and feature extraction methods are applied separately to the terms which are ranked in decreasing order of importance, and a dimension reduction is carried out. Thereby, during text categorization, terms of less importance are ignored, and feature selection and extraction methods are applied to the terms of highest importance; thus, the computational time and complexity of categorization is reduced. To evaluate the effectiveness of dimension reduction methods on our purposed model, experiments are conducted using the k-nearest neighbour (KNN) and C4.5 decision tree algorithm on Reuters-21,578 and Classic3 datasets collection for text categorization. The experimental results show that the proposed model is able to achieve high categorization effectiveness as measured by precision, recall and F-measure. © 2011 Elsevier B.V. All rights reserved.
Uguz F.,University of Konya
General Hospital Psychiatry | Year: 2014
This report presents the successful use of low-dose mirtazapine in the treatment of major depression that developed following severe nausea and vomiting symptoms during the early gestational weeks in two cases. The psychiatric diagnosis was determined with the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Assessments were performed with the Clinical Global Impression - Improvement Scale and the 17-item Hamilton Rating Scale for Depression. Further large-scale studies should be carried out to confirm the useful effects observed in these cases. © 2014 Elsevier Inc.