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Institution

Üsküdar University

EducationSkutari, Turkey
About: Üsküdar University is a education organization based out in Skutari, Turkey. It is known for research contribution in the topics: Electromagnetic shielding & Effective atomic number. The organization has 413 authors who have published 891 publications receiving 9463 citations.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: The results of this study indicate that social phobia was associated with the risk for smartphone addiction in young people and younger individuals who primarily use their smartphones to access social networking sites also have an excessive pattern of smartphone use.
Abstract: Individuals with psychosocial problems such as social phobia or feelings of loneliness might be vulnerable to excessive use of cyber-technological devices, such as smartphones. We aimed to determine the relationship of smartphone addiction with social phobia and loneliness in a sample of university students in Istanbul, Turkey. Three hundred and sixty-seven students who owned smartphones were given the Smartphone Addiction Scale SAS, UCLA Loneliness Scale UCLA-LS, and Brief Social Phobia Scale BSPS. A significant difference was found in the mean SAS scores p < .001 between users who declared that their main purpose for smartphone use was to access social networking sites. The BSPS scores showed positive correlations with all six subscales and with the total SAS scores. The total UCLA-LS scores were positively correlated with daily life disturbance, positive anticipation, cyber-oriented relationship, and total scores on the SAS. In regression analyses, total BSPS scores were significant predictors for SAS total scores β = 0.313, t = 5.992, p < .001. In addition, BSPS scores were significant predictors for all six SAS subscales, whereas UCLA-LS scores were significant predictors for only cyber-oriented relationship subscale scores on the SAS β = 0.130, t = 2.416, p < .05. The results of this study indicate that social phobia was associated with the risk for smartphone addiction in young people. Younger individuals who primarily use their smartphones to access social networking sites also have an excessive pattern of smartphone use.

267 citations

Journal ArticleDOI
TL;DR: The latest literature examining the effects of the gut microbiota on depression is presented, including preclinical research in rodents suggested that certain probiotics have antidepressant and anxiolytic activities.
Abstract: The gut microbiota is essential to human health and the immune system and plays a major role in the bidirectional communication between the gut and the brain. Based on evidence, the gut microbiota is associated with metabolic disorders such as obesity, diabetes mellitus and neuropsychiatric disorders such as schizophrenia, autistic disorders, anxiety disorders and major depressive disorders. In the past few years, neuroscientific research has shown the importance of the microbiota in the development of brain systems. Recent studies showed that the microbiota could activate the immune and central nervous systems, including commensal and pathogenic microorganisms in the gastrointestinal tract. Gut microorganisms are capable of producing and delivering neuroactive substances such as serotonin and gamma-aminobutyric acid, which act on the gut-brain axis. Preclinical research in rodents suggested that certain probiotics have antidepressant and anxiolytic activities. Effects may be mediated via the immune system or neuroendocrine systems. Herein, we present the latest literature examining the effects of the gut microbiota on depression.

217 citations

Journal ArticleDOI
TL;DR: Using Genetic Algorithm (GA) based feature selection method, online technologies self-efficacy, online learning readiness, and previous online experience were found as the most important factors in predicting the dropouts.
Abstract: This study examined the prediction of dropouts through data mining approaches in an online program. The subject of the study was selected from a total of 189 students who registered to the online Information Technologies Certificate Program in 2007-2009. The data was collected through online questionnaires (Demographic Survey, Online Technologies Self-Efficacy Scale, Readiness for Online Learning Questionnaire, Locus of Control Scale, and Prior Knowledge Questionnaire). The collected data included 10 variables, which were gender, age, educational level, previous online experience, occupation, self efficacy, readiness, prior knowledge, locus of control, and the dropout status as the class label (dropout/not). In order to classify dropout students, four data mining approaches were applied based on k-Nearest Neighbour (k-NN), Decision Tree (DT), Naive Bayes (NB) and Neural Network (NN). These methods were trained and tested using 10-fold cross validation. The detection sensitivities of 3-NN, DT, NN and NB classifiers were 87%, 79.7%, 76.8% and 73.9% respectively. Also, using Genetic Algorithm (GA) based feature selection method, online technologies self-efficacy, online learning readiness, and previous online experience were found as the most important factors in predicting the dropouts.

194 citations

Journal ArticleDOI
Hannah Moshontz1, Lorne Campbell2, Charles R. Ebersole3, Hans IJzerman4, Heather L. Urry5, Patrick S. Forscher6, Jon Grahe7, Randy J. McCarthy8, Erica D. Musser9, Jan Antfolk10, Christopher M. Castille11, Thomas Rhys Evans12, Susann Fiedler13, Jessica Kay Flake14, Diego A. Forero, Steve M. J. Janssen15, Justin Robert Keene16, John Protzko17, Balazs Aczel18, Sara Álvarez Solas, Daniel Ansari2, Dana Awlia19, Ernest Baskin20, Carlota Batres21, Martha Lucia Borras-Guevara22, Cameron Brick23, Priyanka Chandel24, Armand Chatard25, Armand Chatard26, William J. Chopik27, David Clarance, Nicholas A. Coles28, Katherine S. Corker29, Barnaby J. W. Dixson30, Vilius Dranseika31, Yarrow Dunham32, Nicholas W. Fox33, Gwendolyn Gardiner34, S. Mason Garrison35, Tripat Gill36, Amanda C. Hahn37, Bastian Jaeger38, Pavol Kačmár39, Gwenaël Kaminski, Philipp Kanske40, Zoltan Kekecs41, Melissa Kline42, Monica A. Koehn43, Pratibha Kujur24, Carmel A. Levitan44, Jeremy K. Miller45, Ceylan Okan43, Jerome Olsen46, Oscar Oviedo-Trespalacios47, Asil Ali Özdoğru48, Babita Pande24, Arti Parganiha24, Noorshama Parveen24, Gerit Pfuhl, Sraddha Pradhan24, Ivan Ropovik49, Nicholas O. Rule50, Blair Saunders51, Vidar Schei52, Kathleen Schmidt53, Margaret Messiah Singh24, Miroslav Sirota54, Crystal N. Steltenpohl55, Stefan Stieger56, Daniel Storage57, Gavin Brent Sullivan12, Anna Szabelska58, Christian K. Tamnes59, Miguel A. Vadillo60, Jaroslava Varella Valentova61, Wolf Vanpaemel62, Marco Antonio Correa Varella61, Evie Vergauwe63, Mark Verschoor64, Michelangelo Vianello65, Martin Voracek46, Glenn Patrick Williams66, John Paul Wilson67, Janis Zickfeld59, Jack Arnal68, Burak Aydin, Sau-Chin Chen69, Lisa M. DeBruine70, Ana María Fernández71, Kai T. Horstmann72, Peder M. Isager73, Benedict C. Jones70, Aycan Kapucu74, Hause Lin50, Michael C. Mensink75, Gorka Navarrete76, Silan Ma77, Christopher R. Chartier19 
Duke University1, University of Western Ontario2, University of Virginia3, University of Grenoble4, Tufts University5, University of Arkansas6, Pacific Lutheran University7, Northern Illinois University8, Florida International University9, Åbo Akademi University10, Nicholls State University11, Coventry University12, Max Planck Society13, McGill University14, University of Nottingham Malaysia Campus15, Texas Tech University16, University of California, Santa Barbara17, Eötvös Loránd University18, Ashland University19, Saint Joseph's University20, Franklin & Marshall College21, University of St Andrews22, University of Cambridge23, Pandit Ravishankar Shukla University24, University of Poitiers25, Centre national de la recherche scientifique26, Michigan State University27, University of Tennessee28, Grand Valley State University29, University of Queensland30, Vilnius University31, Yale University32, Rutgers University33, University of California, Riverside34, Vanderbilt University35, Wilfrid Laurier University36, Humboldt State University37, Tilburg University38, University of Pavol Jozef Šafárik39, Dresden University of Technology40, Lund University41, Massachusetts Institute of Technology42, University of Sydney43, Occidental College44, Willamette University45, University of Vienna46, Queensland University of Technology47, Üsküdar University48, University of Prešov49, University of Toronto50, University of Dundee51, Norwegian School of Economics52, Southern Illinois University Carbondale53, University of Essex54, University of Southern Indiana55, University of Health Sciences Antigua56, University of Illinois at Urbana–Champaign57, Queen's University Belfast58, University of Oslo59, Autonomous University of Madrid60, University of São Paulo61, Katholieke Universiteit Leuven62, University of Geneva63, University of Groningen64, University of Padua65, Abertay University66, Montclair State University67, McDaniel College68, Tzu Chi University69, University of Glasgow70, University of Santiago, Chile71, Humboldt University of Berlin72, Eindhoven University of Technology73, Ege University74, University of Wisconsin–Stout75, Adolfo Ibáñez University76, University of the Philippines Diliman77
01 Oct 2018
TL;DR: The Psychological Science Accelerator is a distributed network of laboratories designed to enable and support crowdsourced research projects that will advance understanding of mental processes and behaviors by enabling rigorous research and systematic examination of its generalizability.
Abstract: Concerns about the veracity of psychological research have been growing. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions or replicate prior research in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time limited), efficient (in that structures and principles are reused for different projects), decentralized, diverse (in both subjects and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside the network). The PSA and other approaches to crowdsourced psychological science will advance understanding of mental processes and behaviors by enabling rigorous research and systematic examination of its generalizability.

180 citations

Journal ArticleDOI
TL;DR: In this article, a comprehensive study of photon interaction features has been made for some alloys containing Pd and Ag content to evaluate its possible use as alternative gamma radiations shielding material.

164 citations


Authors

Showing all 439 results

NameH-indexPapersCitations
Huseyin Ozan Tekin441144116
Shams A.M. Issa311692760
Mustafa Bayram272292515
Muhsin Konuk211332039
Nazan Aydin211171439
Murat Cokol21424898
Gokhan Apaydin211281551
Ozge Kilicoglu21481296
Cumhur Tas1948901
Volkan Turan19831314
Huseyin Ozan Tekin191301146
Tayfun Uzbay18541060
Sultan Tarlaci18481444
Cem Celik1752738
Oğuz Karamustafalıoğlu1769883
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202314
202235
2021198
2020147
2019133
201896