The Forecasting of Labour Force Participation and the Unemployment Rate in Poland and Turkey Using Fuzzy Time Series Methods

Fuzzy time series methods based on the fuzzy set theory proposed by Zadeh (1965) was first introduced by Song and Chissom (1993). Since fuzzy time series methods do not have the assumptions that traditional time series do and have effective forecasting performance, the interest on fuzzy time series approaches is increasing rapidly. Fuzzy time series methods have been used in almost all areas, such as environmental science, economy and finance. The concepts of labour force participation and unemployment have great importance in terms of both the economy and sociology of countries. For this reason there are many studies on their forecasting. In this study, we aim to forecast the labour force participation and unemployment rate in Poland and Turkey using different fuzzy time series methods

Factors Affecting the Outcome in Traumatic Subarachnoid Hemorrhage

Objective: To define risk factors affecting the outcome in traumatic subarachnoid hemorrhage.Material and Methods: Forty-four patients with traumatic subarachnoid hemorrhage were evaluated retrospectively. They were divided into three groups according to their age: elderly (≥65 years), adult (16- 64 years), and children (<16 years). The clinical picture on admission was evaluated using the Glasgow Coma Scale. The patients were also divided into three groups according to their coma grading on admission: mild injury (Glasgow Coma Scale score 13-15), moderate injury (8-12), and severe injury (3-7). The amount of subarachnoid blood shown in computerized tomography was evaluated according to the Fisher index, and additional tomography findings were recorded. At last follow-up, presence of headache and neurological deficits as well as return to work or school were investigated, and the last clinical picture was evaluated with the Glasgow Outcome Scale.Results: There were 11 children, 23 adults and 10 elderly patients. Twelve patients died between 1-49 days after trauma; the others were followed for a mean of 14.6 months (from 10 to 30 months). In the children group, Glasgow Coma Scale score was significantly higher (p=0.004), subarachnoid blood amount was significantly lesser, and Glasgow Outcome Scale score was significantly better compared to the other groups. For all groups, higher trauma severity on admission was associated with higher Fisher index (p=0.016). Most important factors affecting clinical results were severity of head injury on admission (p=0.0001), Fisher index (p=0.003), and presence of additional findings on computerized tomography (p=0.0001).Conclusion: Traumatic subarachnoid hemorrhage usually has a good clinical outcome in children; however, in elderly patients, the outcome is worse, and there are usually additional intracranial traumatic lesions. Most important factors affecting outcome are blood amount on first computerized tomography, head trauma severity, and presence of additional intracranial traumatic lesions

Volume CXIV, Number 4, November 7, 1996

Objective: Turner syndrome (TS) is a chromosomal disorder caused by complete or partial X chromosome monosomy that manifests various clinical features depending on the karyotype and on the genetic background of affected girls. This study aimed to systematically investigate the key clinical features of TS in relationship to karyotype in a large pediatric Turkish patient population.Methods: Our retrospective study included 842 karyotype-proven TS patients aged 0-18 years who were evaluated in 35 different centers in Turkey in the years 2013-2014.Results: The most common karyotype was 45,X (50.7%), followed by 45,X/46,XX (10.8%), 46,X,i(Xq) (10.1%) and 45,X/46,X,i(Xq) (9.5%). Mean age at diagnosis was 10.2±4.4 years. The most common presenting complaints were short stature and delayed puberty. Among patients diagnosed before age one year, the ratio of karyotype 45,X was significantly higher than that of other karyotype groups. Cardiac defects (bicuspid aortic valve, coarctation of the aorta and aortic stenosis) were the most common congenital anomalies, occurring in 25% of the TS cases. This was followed by urinary system anomalies (horseshoe kidney, double collector duct system and renal rotation) detected in 16.3%. Hashimoto's thyroiditis was found in 11.1% of patients, gastrointestinal abnormalities in 8.9%, ear nose and throat problems in 22.6%, dermatologic problems in 21.8% and osteoporosis in 15.3%. Learning difficulties and/or psychosocial problems were encountered in 39.1%. Insulin resistance and impaired fasting glucose were detected in 3.4% and 2.2%, respectively. Dyslipidemia prevalence was 11.4%.Conclusion: This comprehensive study systematically evaluated the largest group of karyotype-proven TS girls to date. The karyotype distribution, congenital anomaly and comorbidity profile closely parallel that from other countries and support the need for close medical surveillance of these complex patients throughout their lifespa

Clinical and Laboratory Characteristics of Hyperprolactinemia in Children and Adolescents: National Survey

Conclusion: We present the largest cohort of children and adolescents with hyperprolactinemia in the literature to date. Hyperprolactinemia is more common in females and cabergoline is highly effective and practical to use in adolescents, due to its biweekly dosing. Indications for surgery in pediatric cases need to be revised

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world’s countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome

Picture fuzzy regression functions approach for financial time series based on ridge regression and genetic algorithm

WOS: 000510957900007Recent years, fuzzy inference systems are efficient tools for solving forecasting problems. Fuzzy inference systems are based on fuzzy sets and use membership values besides original data so a data augmentation mechanism is employed in the fuzzy inference. Picture fuzzy sets provide additional information to original data via positive degree membership, negative degree membership, neutral degree membership and refusal degree membership apart from fuzzy sets. The data augmentation with this additional information will be provided to build a better inference system than fuzzy inference systems. In this study, picture fuzzy inference system is proposed for forecasting purpose by using ridge regression and genetic algorithm. Ridge regression method is used to obtain picture fuzzy functions and genetic algorithm is used to emerge different information coming from systems which are designed for positive degree membership, negative degree membership and neutral degree membership. In the proposed method, picture fuzzification is provided by picture fuzzy clustering. The proposed inference system is tested by various stock exchange data sets. The forecasting of the proposed method is compared with well-known forecasting methods. The obtained results are evaluated according to different error measures such as root of mean square error and mean of absolute percentage error. (C) 2019 Published by Elsevier B.V

Training Sigma-Pi neural networks with the grey wolf optimization algorithm

Artificial neural network models have been frequently used in time series forecasting problems as an alternative to many classical forecasting models. Although multi-layer perceptron neural networks are one of the most frequently used artificial neural networks in the literature, high-order neural networks using high-order combinations of inputs have superior performance compared to multi-layer perceptron artificial neural networks in recent years. Although there are many highorder artificial neural networks with different properties in the literature, one of the most important problems of these highorder artificial neural networks is to determine the optimization method to be used in the training of the network structure. Sigma-Pi artificial neural networks, one of the high-order artificial neural networks, have been used frequently in many problems in recent years. Like many artificial neural networks, the training of the Sigma-Pi neural network is one of the important factors affecting the performance of the network. In this study, the grey wolf optimization algorithm is used for the first time in the literature in the training of Sigma-Pi artificial neural networks. Thus, a training process that does not require complex derivative calculations in derivative-based algorithms is performed. In the evaluation of the performance of the proposed method, the closing prices of the FTSE and S&P 500 are analyzed for different years. According to the analysis results, the proposed method has a 60% success rate for both FTSE and S&P 500 time series. For the comparison of all methods, the mean rank calculation is made for each method. The proposed method took first place in this ranking and is determined as the best method among all methods