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In this study, Mountain Gazelle Optimization (MGO) and Gazelle Optimization Algorithm (GOA) algorithms, which have been newly proposed in recent years, were examined. Although MGO and GOA are different heuristic algorithms, they are often considered the same algorithms by researchers. This study was conducted to resolve this confusion and demonstrate the discovery and exploitation success of both algorithms. While MGO developed the exploration and exploitation ability by being inspired by the behavior of gazelles living in different groups, GOA model was developed by being inspired by the behavior of gazelles in escaping from predators, reaching safe environments and grazing in safe environments. MGO and GOA were tested on 13 classical benchmark functions in seven different dimensions and their success was compared. According to the results, MGO is more successful than GOA in all dimensions. GOA, on the other hand, works faster than MGO. Additionally, MGO and GOA were tested on three different engineering design problems. While MGO was more successful in the tension/compression spring design problem and welded beam design problems, GOA achieved better results in the pressure vessel design problem. The results show that MGO improves the ability to explore and avoid local traps better than GOA. MGO and GOA are also compared with three different heuristic algorithms selected from the literature (GSO, COA, and ZOA). According to the results, MGO has shown that it can compete with new algorithms in the literature. GOA, on the other hand, lags behind comparison algorithms. [ABSTRACT FROM AUTHOR]

Particle Swarm Optimization (PSO) is a commonly used optimization to solve many problems. The PSO, which is developed for continuous optimization, is updated to solve discrete problems and Discrete PSO (DPSO) is obtained in this study. With DPSO, the Traveling Salesman Problem (TSP), which is well-known in the literature as a discrete problem, is solved. In order to improve the results, the swap method, the shift method, and the symmetry method are added to DPSO. The symmetry method is a new and successful method. The variations of the DPSO occurred according to the selected method type (DPSO1 (swap method), DPSO2 (shift method), DPSO3 (swap and shift methods), DPSO4 (symmetry method), DPSO5 (swap, shift, and symmetry methods), DPSO6 (swap, shift, symmetry, and 2-opt methods)). The effect of each method on the performance of the DPSO has been studied in detail. To demonstrate the success of the variations of the DPSO, the results are additionally compared with many well-known and new discrete algorithms in the literature. The results showed that the performance of DPSO has improved with the symmetry method and it has achieved better results than the discrete heuristic algorithms recently proposed in the literature. [ABSTRACT FROM AUTHOR]

In recent times, big data has become an essential concern with the rapid increase of digitalization. The problems that find solutions to the problems of finding and evaluating the features of big data are called optimization problems. In this paper, data sets containing EEG signals have been studied. The goal is to detect actual EEG signals while eliminating additional brain activity patterns in the collected data, resulting in more accurate interpretation. In the study, to handle big data optimization (BigOpt) difficulties, a novel swarm intelligence-based technique is developed. A Developed PSO-Q was proposed by updating the random walking phase of the Particle Swarm Optimization on the combined quantum behaved method (PSO-Q) for BigOpt problems. PSO-Q's local search capability has been improved. The success of PSO-Q and IPSO-Q has been thoroughly tested in various cycles (maximum iterations) (300, 400, 500, and 1000) and population sizes (10, 25, and 50) on six data sets. The outcomes of the PSO-Q and IPSO-Q were statistically evaluated with the Wilcoxon Signed-Rank Test. PSO-Q and IPSO-Q have been compared with newly developed swarm-based algorithms (BA, Jaya, AOA, etc.) in the literature in recent years. The success of IPSO-Q has been shown by evaluating the results obtained. The results showed that IPSO-Q can be used as an alternative algorithm in BigOpt problems. [ABSTRACT FROM AUTHOR]

Today, with the increasing use of technology tools in daily life, big data has gained even more importance. In recent years, many methods have been used to interpret big data. One of them is metaheuristic algorithms. Meta-heuristic methods, which have been used by very few researchers yet, have become increasingly common. In this study, Tunicate Swarm Algorithm (TSA), which has been newly developed in recent years, was chosen to solve big data optimization problems. The Enhanced TSA (ETSA) was obtained by first developing the swarm action of the TSA. In order to show the achievements of TSA and ETSA, various classical benchmark functions were determined from the literature. The success of ETSA has been proven on these benchmark functions. Then, the successes of TSA and ETSA are shown in detail on big datasets containing six different EEG signal data, with five different population sizes (10, 20, 30, 50, 100) and three different stopping criteria (300, 500, 1000). The results were compared with the Jaya, SOA, and SMA algorithms selected from the literature, and the success of ETSA was determined. The results show that ETSA has sufficient success in solving big data optimization problems and continuous optimization problems. [ABSTRACT FROM AUTHOR]

Heuristic algorithms can give optimal solutions for low, middle, and large scale optimization problems in an acceptable time. The social spider algorithm (SSA) is one of the recent meta-heuristic algorithms that imitate the behaviors of the spider to perform global optimization. The original study of this algorithm was proposed to solve low scale continuous problems, and it is not be solved to middle and large scale continuous problems. In this paper, we have improved the SSA and have solved middle and large scale continuous problems, too. By adding two new techniques to the original SSA, the performance of the original SSA has been improved and it is named as an improved SSA (ISSA). In this paper, various unimodal and multimodal standard benchmark functions for low, middle, and large-scale optimization are studied for displaying the performance of ISSA. ISSA's performance is also compared with the well-known and new evolutionary methods in the literature. Test results show that ISSA displays good performance and can be used as an alternative method for large scale optimization. [ABSTRACT FROM AUTHOR]

Purpose: The present study aims to identify the attitudes of men living in two different cities of Turkey towards violence against women and to investigate the variables affecting their attitudes towards violence. Design and Methods: This descriptive and cross‐sectional study was conducted in two factories in Ağrı and Kahramanmaraş cities between October and November 2019. Findings: Participants' ISKEBE Violence against Women Attitude Scale mean score was 98.14 ± 20.30, Attitudes towards Body subscale mean score was 64.73 ± 11.99, and Attitudes towards Identity subscale mean score was 33.41 ± 10.45. Of all the participants, 32.6% demonstrated positive attitudes towards violence against women, and 67.4% demonstrated negative attitudes towards violence against women. Practice Implications: Knowing males' attitudes towards violence against women can contribute to the development of violence policies towards women. [ABSTRACT FROM AUTHOR]

Purpose. To compare one-year treatment outcomes of intravitreal aflibercept (IVA) and intravitreal ranibizumab (IVR) for treatment of myopic choroidal neovascularization (mCNV). Methods. The medical records of a total of 30 eyes diagnosed with mCNV and underwent IVA or IVR treatment for a minimum one-year follow-up were studied retrospectively. All the subjects had an axial length >26 mm and received a 1 + PRN (pro re nata) regimen IVA or IVR. Best-corrected visual acuity (BCVA) and central macular thicknesses (CMT) on optical coherence tomography were evaluated before and after treatment. Results. There were 12 eyes in IVA group, with a mean age of 60.0 ± 10.2 years. The mean BCVA significantly improved from baseline 1.54 ± 0.76 to 0.85 ± 0.61 and the mean CMT significantly decreased from baseline 384.3 ± 119.1 μm to 305.9 ± 75.4 μm at Month 12 (p:0.024 and p:0.011, respectively). There were 18 eyes in IVR group, with a mean age of 57.4 ± 13.1 years. The mean BCVA improved from baseline 1.14 ± 0.90 to 1.04 ± 0.93 and the mean CMT significantly decreased from baseline 366.5 ± 102.3 μm to 323.6 ± 103.6 μm at Month 12 after IVR (p:0.345 and p:0.011, respectively). There was no significant difference between the groups in CMT changes in the study period (p:0.178), but IVA resulted in significantly better final visual gain (0.69 versus 0.09; p:0.006). Conclusions. Both IVA and IVR treatment modalities resulted in similar anatomical outcomes but IVA had better visual outcomes in treatment of mCNV. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is the fifth most common male-predominant type of cancer worldwide. There is no effective treatment regimen available for advanced-stage disease and chemotherapy is generally ineffective in these patients. The number of studies on the prevalence of K-Ras mutations in HCC patients is currently limited. A total of 58 patients from 6 comprehensive cancer centers in 4 metropolitan cities of Turkey were enrolled in this study. Each center committed to enroll approximately 10 random patients whose formalin-fixed parafin-embedded tumor tissues were available for K-Ras, exon 2 genotyping. Two methods were applied based on the availability of adequate amounts of tumor DNA. In the first method, the samples were processed using TheraScreen. The genomic DNA was further used to detect the 7 most frequent somatic mutations (35G>A; 35G>C; 35G>T; 34G>A; 34G>C; 34G>T and 38G>A) in codons 12 and 13 in exon 2 of the K-Ras oncogene by quantitative polymerase chain reaction (PCR). In the second method, the genomic DNA was amplified by PCR using primers specific for K-Ras exon 2 with the GML SeqFinder Sequencing System's KRAS kit. The identified DNA sequence alterations were confirmed by sequencing both DNA strands in two independent experiments with forward and reverse primers. A total of 40 samples had adequate tumor tissue for the mutation analysis. A total of 33 (82.5%) of the investigated samples harbored no mutations in exon 2. All the mutations were identified via a direct sequencing technique, whereas none were identified by TheraScreen. In conclusion, in our patients, HCC exhibited a remarkably low (<20%) K-Ras mutation rate. Patients harboring K-Ras wild-type tumors may be good candidates for treatment with epidermal growth factor inhibitors, such as cetuximab. [ABSTRACT FROM AUTHOR]

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Purpose: To evaluate the efficacy of early switch to intravitreal dexamethasone implantation (IDI) in aflibercept resistant diabetic macular edema (DME) Materials and methods: In this retrospective study 21 eyes of 21 patients with persistent diabetic macular edema, who underwent a single dose IDI were examined. All of the patients had a history of at least five intravitreal aflibercept (IVA) injections. Main outcome measures were changes in best-corrected visual acuity (BCVA), central macular thickness (CMT) at 1, 2, 3 months after IDI treatment. Results: Mean follow-up time and average number of previous IVA injections was 19.24±1.67 months and 5.35±0.6. The mean BCVA was improved from 0.73±0.57logMAR to 0.49±0.34logMAR (p=0.011), 0.34±0.29 logMAR(p=0.001), and 0.36±0.27 logMAR(p=0.001) at 1,2 and 3 months, respectively. The mean CMT was decreased from 434±90 μm to 335±74 μm (p<0.001), 328±46 μm (p<0.001) and 350±85 μm (p=0.009) at 1,2 and 3 months. Conclusion: Intravitreal dexamethasone implantation resulted in a significant improvement in visual and anatomical outcomes in patients with aflibercept resistant diabetic macular edema. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is the fifth most common male-predominant type of cancer worldwide. There is no effective treatment regimen available for advanced-stage disease and chemotherapy is generally ineffective in these patients. The number of studies on the prevalence of K-Ras mutations in HCC patients is currently limited. A total of 58 patients from 6 comprehensive cancer centers in 4 metropolitan cities of Turkey were enrolled in this study. Each center committed to enroll approximately 10 random patients whose formalin-fixed paraffin-embedded tumor tissues were available for K-Ras, exon 2 genotyping. Two methods were applied based on the availability of adequate amounts of tumor DNA. In the first method, the samples were processed using TheraScreen. The genomic DNA was further used to detect the 7 most frequent somatic mutations (35G>A; 35G>C; 35G>T; 34G>A; 34G>C; 34G>T and 38G>A) in codons 12 and 13 in exon 2 of the K-Ras oncogene by quantitative polymerase chain reaction (PCR). In the second method, the genomic DNA was amplified by PCR using primers specific for K-Ras exon 2 with the GML SeqFinder Sequencing System's KRAS kit. The identified DNA sequence alterations were confirmed by sequencing both DNA strands in two independent experiments with forward and reverse primers. A total of 40 samples had adequate tumor tissue for the mutation analysis. A total of 33 (82.5%) of the investigated samples harbored no mutations in exon 2. All the mutations were identified via a direct sequencing technique, whereas none were identified by TheraScreen. In conclusion, in our patients, HCC exhibited a remarkably low (<20%) K-Ras mutation rate. Patients harboring K-Ras wild-type tumors may be good candidates for treatment with epidermal growth factor inhibitors, such as cetuximab.