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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]

Arithmetic Optimization Algorithm (AOA) is a heuristic method developed in recent years. The original version was developed for continuous optimization problems. Its success in binary optimization problems has not yet been sufficiently tested. In this paper, the binary form of AOA (BinAOA) has been proposed. In addition, the candidate solution production scene of BinAOA is developed with the xor logic gate and the BinAOAX method was proposed. Both methods have been tested for success on well-known uncapacitated facility location problems (UFLPs) in the literature. The UFL problem is a binary optimization problem whose optimum results are known. In this study, the success of BinAOA and BinAOAX on UFLP was demonstrated for the first time. The results of BinAOA and BinAOAX methods were compared and discussed according to best, worst, mean, standard deviation, and gap values. The results of BinAOA and BinAOAX on UFLP are compared with binary heuristic methods used in the literature (TSA, JayaX, ISS, BinSSA, etc.). As a second application, the performances of BinAOA and BinAOAX algorithms are also tested on classical benchmark functions. The binary forms of AOA, AOAX, Jaya, Tree Seed Algorithm (TSA), and Gray Wolf Optimization (GWO) algorithms were compared in different candidate generation scenarios. The results showed that the binary form of AOA is successful and can be preferred as an alternative binary heuristic method. [ABSTRACT FROM AUTHOR]

Recently, researchers have started to be interested in population-based swarm-based algorithms in optimization due to their simple structure, high optimization performance, and ease of adaptation. Although swarm-based algorithms solve continuous optimization problems, they can also be used to solve binary optimization problems. In continuous optimization, the search space variables try to approach the optimal value, while in discrete optimization, the search space variables are fixed and expressed with real values. In binary optimization, the decision variables take values of 0 and 1 and are basically in the discrete optimization class. In this paper, the proposed Rat Swarm Algorithm (RSA) to solve continuous optimization problems is examined. RSA is an algorithm based on swarm intelligence. RSA was developed by imitating the chasing and attacking behaviors of rats. In this study, the original RSA was updated again to solve binary optimization problems and Binary RSA (BinRSA) was proposed. In BinRSA, four U-shaped and four T-shaped transfer functions are used while converting the continuous search field values to binary values. Thus, eight variants of BinRSA were obtained. These are named as BinRSA1, BinRSA2, BinRSA3, BinRSA4, BinRSA5, BinRSA6, BinRSA7 and BinRSA8. Among these variants, the most successful variant of BinRSA was determined as BinRSA6. Then the BinRSA6 variant was developed by adding crossover and mutation operators and was named GBinRSA. GBinRSA's performance has been tested in knapsack problems. In addition, the success of GBinRSA was compared with different heuristic algorithms selected from the literature. According to the results obtained, it has been seen that the solution quality of the proposed algorithm is effective and comparable. The results showed that GBinRSA is a preferred heuristic for binary optimization 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]

The social spider algorithm (SSA) is a new heuristic algorithm created on spider behaviors. The original study of this algorithm was proposed to solve continuous problems. In this paper, the binary version of SSA (binary SSA) is introduced to solve binary problems. Currently, there is insufficient focus on the binary version of SSA in the literature. The main part of the binary version is at the transfer function. The transfer function is responsible for mapping continuous search space to discrete search space. In this study, four of the transfer functions divided into two families, S-shaped and V-shaped, are evaluated. Thus, four different variations of binary SSA are formed as binary SSA-Tanh, binary SSA-Sigm, binary SSA-MSigm and binary SSA-Arctan. Two different techniques (SimSSA and LogicSSA) are developed at the candidate solution production schema in binary SSA. SimSSA is used to measure similarities between two binary solutions. With SimSSA, binary SSA's ability to discover new points in search space has been increased. Thus, binary SSA is able to find global optimum instead of local optimums. LogicSSA which is inspired by the logic gates and a popular method in recent years has been used to avoid local minima traps. By these two techniques, the exploration and exploitation capabilities of binary SSA in the binary search space are improved. Eighteen unimodal and multimodal standard benchmark optimization functions are employed to evaluate variations of binary SSA. To select the best variations of binary SSA, a comparative study is presented. The Wilcoxon signed-rank test has applied to the experimental results of variations of binary SSA. Compared to well-known evolutionary and recently developed methods in the literature, the variations of binary SSA performance is quite good. In particular, binary SSA-Tanh and binary SSA-Arctan variations of binary SSA showed superior performance. [ABSTRACT FROM AUTHOR]

The optimization process entails determining the best values for various system characteristics in order to finish the system design at the lowest possible cost. In general, real-world applications and issues in artificial intelligence and machine learning are discrete, unconstrained, or discrete. Optimization approaches have a high success rate in tackling such situations. As a result, several sophisticated heuristic algorithms based on swarm intelligence have been presented in recent years. Various academics in the literature have worked on such algorithms and have effectively addressed many difficulties. Aquila Optimizer (AO) is one such algorithm. Aquila Optimizer (AO) is a recently suggested heuristic algorithm. It is a novel population-based optimization strategy. It was made by mimicking the natural behavior of the Aquila. It was created by imitating the behavior of the Aquila in nature in the process of catching its prey. The AO algorithm is an algorithm developed to solve continuous optimization problems in their original form. In this study, the AO structure has been updated again to solve binary optimization problems. Problems encountered in the real world do not always have continuous values. It exists in problems with discrete values. Therefore, algorithms that solve continuous problems need to be restructured to solve discrete optimization problems as well. Binary optimization problems constitute a subgroup of discrete optimization problems. In this study, a new algorithm is proposed for binary optimization problems (BAO). The most successful BAO-T algorithm was created by testing the success of BAO in eight different transfer functions. Transfer functions play an active role in converting the continuous search space to the binary search space. BAO has also been developed by adding candidate solution step crossover and mutation methods (BAO-CM). The success of the proposed BAO-T and BAO-CM algorithms has been tested on the knapsack problem, which is widely selected in binary optimization problems in the literature. Knapsack problem examples are divided into three different benchmark groups in this study. A total of sixty-three low, medium, and large scale knapsack problems were determined as test datasets. The performances of BAO-T and BAO-CM algorithms were examined in detail and the results were clearly shown with graphics. In addition, the results of BAO-T and BAO-CM algorithms have been compared with the new heuristic algorithms proposed in the literature in recent years, and their success has been proven. According to the results, BAO-CM performed better than BAO-T and can be suggested as an alternative algorithm for solving binary optimization problems. [ABSTRACT FROM AUTHOR]

• Binary Social Spider Algorithm has been developed. • Algorithm is developed by adding similarity measure and logic-gate techniques. • The uncapacitated facility location problems (UFLPs) are solved. • The developed algorithm has shown superior performance. In order to find efficient solutions to real complex world problems, computer sciences and especially heuristic algorithms are often used. Heuristic algorithms can give optimal solutions for large scale optimization problems in an acceptable period. Social Spider Algorithm (SSA), which is a heuristic algorithm created on spider behaviors are studied. The original study of this algorithm was proposed to solve continuous problems. In this paper, the binary version of the Social Spider Algorithm called Binary Social Spider Algorithm (BinSSA) is proposed for binary optimization problems. BinSSA is obtained from SSA, by transforming constant search space to binary search space with four transfer functions. Thus, BinSSA variations are created as BinSSA1, BinSSA2, BinSSA3, and BinSSA4. The study steps of the original SSA are re-updated for BinSSA. A random walking schema in SSA is replaced by a candidate solution schema in BinSSA. Two new methods (similarity measure and logic gate) are used in candidate solution production schema for increasing the exploration and exploitation capacity of BinSSA. The performance of both techniques on BinSSA is examined. BinSSA is named as BinSSA(Sim&Logic). Local search and global search performance of BinSSA is increased by these two methods. Three different studies are performed with BinSSA. In the first study, the performance of BinSSA is tested on the classic eighteen unimodal and multimodal benchmark functions. Thus, the best variation of BinSSA and BinSSA(Sim&Logic) is determined as BinSSA4(Sim&Logic). BinSSA4(Sim&Logic) has been compared with other heuristic algorithms on CEC2005 and CEC2015 functions. In the second study, the uncapacitated facility location problems (UFLPs) are solved with BinSSA(Sim&Logic). UFL problems are one of the pure binary optimization problems. BinSSA is tested on low-scaled, middle-scaled, and large-scaled fifteen UFLP samples and obtained results are compared with eighteen state-of-art algorithms. In the third study, we solved UFL problems on a different dataset named M* with BinSSA(Sim&Logic). The results of BinSSA(Sim&Logic) are compared with the Local Search (LS), Tabu Search (TS), and Improved Scatter Search (ISS) algorithms. Obtained results have shown that BinSSA offers quality and stable solutions. [ABSTRACT FROM AUTHOR]

• A new binary social spider algorithm (BinSSA) has been developed. • BinSSA is developed by adding a crossover operator. • The developed algorithm has shown superior performance. The social spider algorithm (SSA) is a heuristic algorithm created on spider behaviors to solve continuous problems. In this paper, firstly a binary version of the social spider algorithm called binary social spider algorithm (BinSSA) is proposed. Currently, there is insufficient focus on the binary version of SSA in the literature. The main part of the binary version is the transfer function. The transfer function is responsible for mapping continuous search space to binary search space. In this study, eight of the transfer functions divided into two families, S-shaped and V-shaped, are evaluated. BinSSA is obtained from SSA, by transforming constant search space to binary search space with eight different transfer functions (S-Shapes and V-Shaped). Thus, eight different variations of BinSSA are formed as BinSSA1, BinSSA2, BinSSA3, BinSSA4, BinSSA5, BinSSA6, BinSSA7, and BinSSA8. For increasing, exploration and exploitation capacity of BinSSA, a crossover operator is added as BinSSA-CR. In secondly, the performances of BinSSA variations are tested on feature selection task. The optimal subset of features is a challenging problem in the process of feature selection. In this paper, according to different comparison criteria (mean of fitness values, the standard deviation of fitness values, the best of fitness values, the worst of fitness values, accuracy values, the mean number of the selected features, CPU time), the best BinSSA variation is detected. In the feature selection problem, the K-nearest neighbor (K-NN) and support vector machines (SVM) are used as classifiers. A detailed study is performed for the fixed parameter values used in the fitness function. BinSSA is evaluated on low-scaled, middle-scaled and large-scaled twenty-one well-known UCI datasets and obtained results are compared with state-of-art algorithms in the literature. Obtained results have shown that BinSSA and BinSSA-CR show superior performance and offer quality and stable solutions. [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]

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 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 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]

Objective: The microscopic and macroscopic features of placenta can contribute to the clinical understanding of premature delivery. The aim of our study was to relate the histopathological findings in the placentas of premature infants to pregnancy and explore its relation to neonatal morbidity. Materials and Methods: Placentas of 86 singleton preterm infants were examined and the association between placental pathology and the initiator of the preterm delivery such as preterm labor (PTL), preterm premature rupture of membranes (P-PROM) and pregnancy induced hypertension (PIH) were evaluated. The findings associated with acute placental inflammation or placental evidence of PIH were correlated to the initiators of preterm delivery and the clinical findings of the neonates. Results: The initiator of preterm delivery was PTL in 45%, P-PROM in 20% and PIH in 21% of the infants. Twenty percent of placentas had one or more findings associated with acute inflammation, 43% had findings associated with PIH, 23% had no identifiable pathology and 14% had other findings (intervillous thrombus, villous edema, etc.). Among mothers with placental evidence of acute inflammation, 56% had P-PROM, 38% had PTL and 6% had PIH. The mothers who had histological chorioamnionitis delivered at a younger gestational age than the mothers who had placental evidence of PIH (29 and 32 weeks, respectively; p=0.001). Histological chorioamnionitis was found to be more frequent in the placentas of infants with bronchopulmonary dysplasia (p=0.001). Discussion: This preliminary study revealed that the placental pathological findings appear to be correlated to the initiator of preterm delivery. Examination of the preterm delivery placentas gains importance in determining the etiology of preterm delivery and morbidity in infants. [ABSTRACT FROM AUTHOR]