00907nam0 22002651i 450 UON0022201220231205103419.2720030730d1967 |0itac50 bahunHU|||| |||||Húsz óraSánta Ferenc3 kiadBudapestMagveto Könyvkiadó1967214 p.18 cm.HUBudapestUONL000090894.511Letteratura ungherese21SANTAFerencUONV134510685537Magveto KönyvkiadóUONV274244650ITSOL20240220RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00222012SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI UNGHERESE A SANT 0001 SI FU 464 5 0001 Húsz óra1268402UNIOR06158nam 2200805 450 991080836570332120231222080804.01-118-52131-51-118-52126-9(CKB)3710000000648522(EBL)4504059(SSID)ssj0001646050(PQKBManifestationID)16416028(PQKBTitleCode)TC0001646050(PQKBWorkID)14875627(PQKB)11436323(PQKBManifestationID)16277038(PQKBWorkID)14875626(PQKB)21313423(MiAaPQ)EBC4504059(DLC) 2016002202(Au-PeEL)EBL4504059(CaPaEBR)ebr11202410(CaONFJC)MIL917062(OCoLC)946788600(EXLCZ)99371000000064852220160421h20162016 uy 0engur|n|---|||||txtccrGreat myths of intimate relationships dating, sex, and marriage /Matthew D. JohnsonChichester, West Sussex, England :Wiley Blackwell,2016.©20161 online resource (277 p.)Great Myths of PsychologyTHEi Wiley ebooksDescription based upon print version of record.1-118-52127-7 1-118-52128-5 Includes bibliographical references and indexes.Title Page; Table of Contents; ACKNOWLEDGMENTS; INTRODUCTION; 1 SEX; Myth #1 Men have a stronger libido than women; Myth #2 Hooking up in college is bad for women; Myth #3 All marriages have been consummated; Myth #4 All marriages are sexually active; 2 ATTRACTION AND COURTSHIP; Myth #5 Being smooth is the best way to pick someone up; Myth #6 Opposites attract; Myth #7 People know what they want in a partner; 3 ONLINE DATING; Myth #8 Having access to innumerable online profiles of potential partners increases the likelihood of finding Mr. or Ms. RightMyth #9 Meeting potential partners electronically prior to meeting them in person decreases the chances of a successful relationshipMyth #10 Couples who are "matched" by online dating services are more likely to have satisfying relationships; 4 SAME-SEX RELATIONSHIPS; Myth #11 The gender to which people are attracted is stable (or: the gender to which people are attracted is fluid); Myth #12 There are no differences between same-sex relationships and heterosexual relationships; Myth #13 Children raised by other-sex couples are better off than children raised by same-sex couples5 PREDICTING SUCCESS AND FAILURE IN RELATIONSHIPSMyth #14 Living together before marriage is a good way to determine whether you're with the right person; Myth #15 Premarital counseling or relationship education programs prevent discord and divorce; Myth #16 Good communication is the key to a happy relationship; Myth #17 The key to a good relationship is knowing how to solve your problems; Myth #18 Having children brings couples closer; Myth #19 Stress is bad for relationships; Myth #20 Supporting your partner will improve your relationship; 6 DIFFERENCES, DISCORD, AND DISSOLUTIONMyth #21 Men are from Mars, women are from VenusMyth #22 Only men perpetrate violence in intimate relationships; Myth #23 Marital therapy doesn't work; Myth #24 The first cut is the deepest; Myth #25 Things will improve once you're divorced; CODA; REFERENCES; AUTHOR INDEX; SUBJECT INDEX; End User License Agreement"Great Myths of Intimate Relationships provides a captivating, pithy introduction to the subject that challenges and demystifies the many fabrications and stereotypes surrounding relationships, attraction, sex, love, internet dating, and heartbreak. The book thoroughly interrogates the current research on topics such as attraction, sex, love, internet dating, and heartbreak Takes an argument driven approach to the study of intimate relationships, encouraging critical engagement with the subject Part of The Great Myths series, it's written in a style that is compelling and succinct, making it ideal for general readers and undergraduates "-- Provided by publisher."Intimate relationships is an area heavily cloaked in misconceptions, many of which are relayed as concrete truths; for example, opposites attract, preventing disagreements is vital to a good relationship, and having children can save a marriage. Even some of the most intuitive theories have proved to be wrong or at least much more complicated than the prevailing wisdom, and partially or completely contradicted by scientific research. Great Myths of Intimate Relationships is structured around demystifying the fabrications and stereotypes that dominate the popular understanding of love. Drawing on the very latest studies, and making use of empirical research, the book lays out, reviews and debunks some of the most persistent misconceptions through examining their origins and developments. Johnson explores the current research on topics such as attraction, sex, love, internet dating, and heartbreak, encouraging critical thinking about the science of intimate relationships. Written in a style that is both compelling and succinct, Great Myths of Intimate Relationships is an ideal resource for the interested reader as well as undergraduates of related courses"-- Provided by publisher.Great myths of psychology.THEi Wiley ebooks.LoveSexInterpersonal attractionDating (Social customs)MarriageLove.Sex.Interpersonal attraction.Dating (Social customs)Marriage.306.7PSY041000bisacshJohnson Matthew D.1978-1595318MiAaPQMiAaPQMiAaPQBOOK9910808365703321Great myths of intimate relationships3916190UNINA05853nam 22008655 450 991099649340332120250414132319.03-031-88036-610.1007/978-3-031-88036-0(CKB)38429206200041(DE-He213)978-3-031-88036-0(MiAaPQ)EBC32010384(Au-PeEL)EBL32010384(EXLCZ)993842920620004120250414d2025 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierAnalysis of Images, Social Networks and Texts 12th International Conference, AIST 2024, Bishkek, Kyrgyzstan, October 17–19, 2024, Revised Selected Papers /edited by Alexander Panchenko, Dmitriy Gubanov, Michael Khachay, Andrey Kutuzov, Natalia Loukachevitch, Andrey Kuznetsov, Irina Nikishina, Maxim Panov, Panos M. Pardalos, Andrey V. Savchenko, Evgenii Tsymbalov, Elena Tutubalina, Aida Kasieva, Dmitry I. Ignatov1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (XX, 275 p. 59 illus., 50 illus. in color.) Lecture Notes in Computer Science,1611-3349 ;154193-031-88035-8 -- Keynote and Invited Papers. -- KyrgyzNLP: Challenges, Progress, and Future. -- Modeling Information Influence and Control in Social Networks: Integrating Opinions, Trust, Reputation, and Agent Dynamics. -- Natural Language Processing. -- Graphical Abbreviation Disclosure in Russian Language. -- Iterative Improvement of an Additively Regularized Topic Model. -- Key Algorithms for Keyphrase Generation: Instruction-Based LLMs for Russian Scientific Keyphrases. -- Shrink the longest: improving latent space isotropy with simplicial geometry. -- Redefining Annotation Practices: Leveraging Large Language Models for Discourse Annotation. -- GERA: a corpus of Russian school texts annotated for Grammatical Error Correction. -- From Tokens to Tales: Semantic Similarity in Story Generation. -- Cross-Language Summarization in Russian and Chinese Using the Reinforcement Learning. -- Computer Vision. -- Temporal Modeling via TCN and Transformer for Audio-Visual Emotion Recognition. -- YOLO-HTR: Page-Level Recognition of Historical Handwritten Document Collections. -- Data Analysis and Machine Learning. -- An optimal set of implications in triadic contexts. -- Uniting contrastive and generative learning for event sequences models. -- Theoretical Machine Learning and Optimization. -- An asymptotically optimal algorithm for the minimum weight spanning tree with arbitrarily bounded diameter on random inputs. -- Automatic Adaptive Conformal Inference for Time Series Forecasting.This book constitutes the refereed proceedings of the 12th International Conference on Analysis of Images, Social Networks and Texts, AIST 2024, held in Bishkek, Kyrgyzstan, during October 17–19, 2024. The 16 full papers included in this book were carefully reviewed and selected from 70 submissions. They were organized in topical sections as follows: Natural Language Processing; Computer Vision; Data Analysis and Machine Learning; and Theoretical Machine Learning and Optimization.Lecture Notes in Computer Science,1611-3349 ;15419Data miningMachine learningDatabase managementNatural language processing (Computer science)Information storage and retrieval systemsApplication softwareData Mining and Knowledge DiscoveryMachine LearningDatabase ManagementNatural Language Processing (NLP)Information Storage and RetrievalComputer and Information Systems ApplicationsData mining.Machine learning.Database management.Natural language processing (Computer science)Information storage and retrieval systems.Application software.Data Mining and Knowledge Discovery.Machine Learning.Database Management.Natural Language Processing (NLP).Information Storage and Retrieval.Computer and Information Systems Applications.006.312Panchenko Alexanderedthttp://id.loc.gov/vocabulary/relators/edtGubanov Dmitriyedthttp://id.loc.gov/vocabulary/relators/edtKhachay Michaeledthttp://id.loc.gov/vocabulary/relators/edtKutuzov Andreyedthttp://id.loc.gov/vocabulary/relators/edtLoukachevitch Nataliaedthttp://id.loc.gov/vocabulary/relators/edtKuznetsov Andreyedthttp://id.loc.gov/vocabulary/relators/edtNikishina Irinaedthttp://id.loc.gov/vocabulary/relators/edtPanov Maximedthttp://id.loc.gov/vocabulary/relators/edtPardalos Panos Medthttp://id.loc.gov/vocabulary/relators/edtSavchenko Andrey Vedthttp://id.loc.gov/vocabulary/relators/edtTsymbalov Evgeniiedthttp://id.loc.gov/vocabulary/relators/edtTutubalina Elenaedthttp://id.loc.gov/vocabulary/relators/edtKasieva Aidaedthttp://id.loc.gov/vocabulary/relators/edtIgnatov Dmitry Iedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910996493403321Analysis of images, social networks and texts1907262UNINA