Istanbul University

About: Istanbul University is a education organization based out in Istanbul, Turkey. It is known for research contribution in the topics: Population & Medicine. The organization has 19050 authors who have published 38464 publications receiving 727640 citations. The organization is also known as: İstanbul Üniversitesi & University of Istanbul.

Post-collisional plutonism with adakite-like signatures: the Eocene Saraycık granodiorite (Eastern Pontides, Turkey)

Abstract: The post-collisional Saraycik granodiorite intruded into a late Paleocene to early Eocene nappe pile that formed during collision of the Pontides in the North and the Anatolide-Tauride platform in the South, leading to the formation of the Izmir-Ankara-Erzincan suture. A relatively shallow pluton intrusion depth (∼5 to 8 km) was estimated from Al-in-hornblende geobarometry and contact metamorphic assemblages. The emplacement age is tightly constrained to ∼52 Ma by two Ar–Ar plateau and total fusion ages on biotite. The main mass of the pluton consists of metaluminous to peraluminous biotite granodiorite and hornblende-biotite granodiorite. In addition, up to 10-m thick dacitic and <25-cm thick aplitic dikes occur. Granodiorites and dacites show many close compositional similarities to high-silica adakites from supra-subduction zone settings, but tend to be slightly more felsic and to have a higher aluminium saturation index. Chondrite-normalized (cn) rare earth element patterns are characterized by high ratios of (La/Yb)cn, concave-upward shapes of the HREE and a lack of significant Eu anomalies. In conjunction with relatively high abundances of Ba and Sr as well as low abundances of Y, HREE and Sc, these patterns suggest a feldspar-poor, garnet ± amphibole-rich fractionating mineral assemblage (residue). All samples have very similar Nd–Sr isotopic characteristics, regardless of rock type. Initial eNd values range from −0.3 to −1.2 and initial 87Sr/86Sr ratios from 0.70491 to 0.70529. It is suggested that the magmas formed by partial melting of mafic lower crust at elevated pressures (∼1 to 2 GPa).

Theory of Mind and Neurodevelopmental Disorders of Childhood

Abstract: To a large extent, the human infant is socialized through the acquisition of a specific cognitive mechanism known as theory of mind (ToM), a term which is currently used to explain a related set of intellectual abilities that enable us to understand that others have beliefs, desires, plans, hopes, information, and intentions that may differ from our own. Various neurodevelopmental disorders, such as autism spectrum disorders, attention deficit hyperactivity disorder, developmental language disorders, and schizophrenia, as well as acquired disorders of the right brain (and traumatic brain injury) impair ToM. ToM is a composite function, which involves memory, joint attention, complex perceptual recognition (such as face and gaze processing), language, executive functions (such as tracking of intentions and goals and moral reasoning), emotion processing-recognition, empathy, and imitation. Hence, ToM development is dependent on the maturation of several brain systems and is shaped by parenting, social relations, training, and education; thus, it is an example of the dense interaction that occurs between brain development and (social) environment.

Subjective health, symptom load and quality of life of children and adolescents in Europe.

Abstract: Objectives: To examine cross-cultural differences in the prevalence of school children's subjective health types and the pattern of socio-demographic and socio-economic differences.

Evaluation of face recognition techniques using PCA, wavelets and SVM

Abstract: In this study, we present an evaluation of using various methods for face recognition. As feature extracting techniques we benefit from wavelet decomposition and Eigenfaces method which is based on Principal Component Analysis (PCA). After generating feature vectors, distance classifier and Support Vector Machines (SVMs) are used for classification step. We examined the classification accuracy according to increasing dimension of training set, chosen feature extractor-classifier pairs and chosen kernel function for SVM classifier. As test set we used ORL face database which is known as a standard face database for face recognition applications including 400 images of 40 people. At the end of the overall separation task, we obtained the classification accuracy 98.1% with Wavelet-SVM approach for 240 image training set.