109 research outputs found
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Production and characterization of in-situ Al-NbB2 composites
Data availability: Data will be made available on request.Copyright © 2022 The Author(s). We report here a melt processing route for the production of Al-NbB2 and Al-Cu-NbB2 in-situ composites in which fine NbB2 particles are uniformly distributed in Al matrix. During solidification, in-situ formed NbB2 phase in liquid Al contributed for enhanced heterogeneous nucleation, which caused a dramatic refinement of primary Al grain size, uniformly distributed second phases and enhanced wear characteristics.TUBITAK under Grant 2219. UK Engineering and Physical Science Research Council (EPSRC Grant: The Future Liquid Metal Engineering Research Hub, grant number: EP/N007638/1)
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Production and Properties of Al/NbB2 In-situ Composite
Öz: Bu çalışmada in-situ yöntemi ile Al matriste NbB2 partikül takviyeli kompozitler üretilmiştir. Farklı oranlarda partikül takviyesinin ve üretim süresinin kompozitler üzerindeki etkileri incelenmiştir. Oluşan partiküller, boyutları ve dağılımları incelenmiş, tane boyutu ve sertliğe etkisi belirlenmiştir. Yapılan çalışmalar neticesinde partikül oluşumunda karıştırma süresinin kullanılan alaşım oranı gibi önemli olduğu belirlenmiş ve en iyi değerler 1,5 saat karıştırma sonucu oluşan %3,75 NbB2 ilaveli kompozitte elde edilmiştir. Bu kompozitte tane boyutu 112 μm seviyelerine inmiştir ve sertlik 306,4 MPa olmuştur.In this study, NbB2 particle reinforced composites in Al matrix were produced by in-situ method. The effects of particle reinforcement at different ratios and production time on composites were investigated. The size and spatial distribution of the formed particles were examined, and the effect on grain size and hardness was determined. As a result of the studies, it was determined that the mixing time is as important as the alloying ratio in the formation of particles, and the best values were obtained in the 3.75% NbB2 added composite, which was formed after 1.5 hours of mixing. In this composite, the grain size was reduced to 112 μm and the hardness was 306.4 MPa.Bu çalışma Karabük Üniversitesi Bilimsel Araştırma Projeleri Koordinatörlüğü'nce FDT-2020-2288 kodlu proje kapsamında desteklenmiştir. Ayrıca 2219 proje kapsamındaki desteğinden dolayı TÜBİTAK’a teşekkür ederiz
Predictors of enhancing human physical attractiveness: Data from 93 countries
People across the world and throughout history have gone to great lengths to enhance their physical appearance. Evolutionary psychologists and ethologists have largely attempted to explain this phenomenon via mating preferences and strategies. Here, we test one of the most popular evolutionary hypotheses for beauty-enhancing behaviors, drawn from mating market and parasite stress perspectives, in a large cross-cultural sample. We also test hypotheses drawn from other influential and non-mutually exclusive theoretical frameworks, from biosocial role theory to a cultural media perspective. Survey data from 93,158 human participants across 93 countries provide evidence that behaviors such as applying makeup or using other cosmetics, hair grooming, clothing style, caring for body hygiene, and exercising or following a specific diet for the specific purpose of improving one physical attractiveness, are universal. Indeed, 99% of participants reported spending >10 min a day performing beauty-enhancing behaviors. The results largely support evolutionary hypotheses: more time was spent enhancing beauty by women (almost 4 h a day, on average) than by men (3.6 h a day), by the youngest participants (and contrary to predictions, also the oldest), by those with a relatively more severe history of infectious diseases, and by participants currently dating compared to those in established relationships. The strongest predictor of attractiveness-enhancing behaviors was social media usage. Other predictors, in order of effect size, included adhering to traditional gender roles, residing in countries with less gender equality, considering oneself as highly attractive or, conversely, highly unattractive, TV watching time, higher socioeconomic status, right-wing political beliefs, a lower level of education, and personal individualistic attitudes. This study provides novel insight into universal beauty-enhancing behaviors by unifying evolutionary theory with several other complementary perspectives.info:eu-repo/semantics/publishedVersio
Seismic resistance of traditional timber-frame hımış
Hımış structures have hardly ever found as extensive a role as other traditional timber housing, such as those originating from Japan or Central Europe, within the wide discourse on the seismic performance of timber-frame architecture that has gained significant momentum in the last few decades owing to advancing testing technologies. While the hımış construction technique was perhaps not born as a result of a conscious search for a seismically resistant building form, it was soon widely appreciated for its structural features advantageous under seismic loading - especially from the sixteenth century when it has become a well-established construction technique in part of the Balkans and in today’s Turkey. Despite widely available anecdotal information based on post-disaster studies regarding its performance under earthquakes, robust quantitative data on the seismic behaviour of these structures were practically non-existent until quite recently, and are still somewhat limited. However, we are now able to confirm that hımış constructions do have intrinsic qualities that are very beneficial under seismic action. This paper aims to make a brief review of the current state of our knowledge on structural performance of hımış buildings under earthquake loading, with specific emphasis on infill/cladding techniques, connection details and energy dissipation characteristics
Validation of the Short Version (TLS-15) of the Triangular Love Scale (TLS-45) Across 37 Languages
Love is a phenomenon that occurs across the world and affects many aspects of human life, including the choice of, and process of bonding with, a romantic partner. Thus, developing a reliable and valid measure of love experiences is crucial. One of the most popular tools to quantify love is Sternberg’s 45-item Triangular Love Scale (TLS-45), which measures three love components: intimacy, passion, and commitment. However, our literature review reveals that most studies (64%) use a broad variety of shortened versions of the TLS-45. Here, aiming to achieve scientific consensus and improve the reliability, comparability, and generalizability of results across studies, we developed a short version of the scale—the TLS-15—comprised of 15 items with 5-point, rather than 9-point, response scales. In Study 1 (N = 7,332), we re-analyzed secondary data from a large-scale multinational study that validated the original TLS-45 to establish whether the scale could be truncated. In Study 2 (N = 307), we provided evidence for the three-factor structure of the TLS-15 and its reliability. Study 3 (N = 413) confirmed convergent validity and test–retest stability of the TLS-15. Study 4 (N = 60,311) presented a large-scale validation across 37 linguistic versions of the TLS-15 on a cross-cultural sample spanning every continent of the globe. The overall results provide support for the reliability, validity, and cross-cultural invariance of the TLS-15, which can be used as a measure of love components—either separately or jointly as a three-factor measure
Predictors of Enhancing Human Physical Attractiveness: Data from 93 Countries
People across the world and throughout history have gone to great lengths to enhance their physical appearance. Evolutionary psychologists and ethologists have largely attempted to explain this phenomenon via mating preferences and strategies. Here, we test one of the most popular evolutionary hypotheses for beauty-enhancing behaviors, drawn from mating market and parasite stress perspectives, in a large cross-cultural sample. We also test hypotheses drawn from other influential and non-mutually exclusive theoretical frameworks, from biosocial role theory to a cultural media perspective. Survey data from 93,158 human participants across 93 countries provide evidence that behaviors such as applying makeup or using other cosmetics, hair grooming, clothing style, caring for body hygiene, and exercising or following a specific diet for the specific purpose of improving ones physical attractiveness, are universal. Indeed, 99% of participants reported spending \u3e10 min a day performing beauty-enhancing behaviors. The results largely support evolutionary hypotheses: more time was spent enhancing beauty by women (almost 4 h a day, on average) than by men (3.6 h a day), by the youngest participants (and contrary to predictions, also the oldest), by those with a relatively more severe history of infectious diseases, and by participants currently dating compared to those in established relationships. The strongest predictor of attractiveness-enhancing behaviors was social media usage. Other predictors, in order of effect size, included adhering to traditional gender roles, residing in countries with less gender equality, considering oneself as highly attractive or, conversely, highly unattractive, TV watching time, higher socioeconomic status, right-wing political beliefs, a lower level of education, and personal individualistic attitudes. This study provides novel insight into universal beauty-enhancing behaviors by unifying evolutionary theory with several other complementary perspectives
Exploring Attitudes Toward “Sugar Relationships” Across 87 Countries: A Global Perspective on Exchanges of Resources for Sex and Companionship
The current study investigates attitudes toward one form of sex for resources: the so-called sugar relationships, which often involve exchanges of resources for sex and/or companionship. The present study examined associations among attitudes toward sugar relationships and relevant variables (e.g., sex, sociosexuality, gender inequality, parasitic exposure) in 69,924 participants across 87 countries. Two self-report measures of Acceptance of Sugar Relationships (ASR) developed for younger companion providers (ASR-YWMS) and older resource providers (ASR-OMWS) were translated into 37 languages. We tested cross-sex and cross-linguistic construct equivalence, cross-cultural invariance in sex differences, and the importance of the hypothetical predictors of ASR. Both measures showed adequate psychometric properties in all languages (except the Persian version of ASR-YWMS). Results partially supported our hypotheses and were consistent with previous theoretical considerations and empirical evidence on human mating. For example, at the individual level, sociosexual orientation, traditional gender roles, and pathogen prevalence were significant predictors of both ASR-YWMS and ASR-OMWS. At the country level, gender inequality and parasite stress positively predicted the ASR-YWMS. However, being a woman negatively predicted the ASR-OMWS, but positively predicted the ASR-YWMS. At country-level, ingroup favoritism and parasite stress positively predicted the ASR-OMWS. Furthermore, significant cross-subregional differences were found in the openness to sugar relationships (both ASR-YWMS and ASR-OMWS scores) across subregions. Finally, significant differences were found between ASR-YWMS and ASR-OMWS when compared in each subregion. The ASR-YWMS was significantly higher than the ASR-OMWS in all subregions, except for Northern Africa and Western Asia
Towards crystal structure prediction of complex organic compounds - a report on the fifth blind test
Following on from the success of the previous crystal structure prediction blind tests (CSP1999, CSP2001, CSP2004 and CSP2007), a fifth such collaborative project (CSP2010) was organized at the Cambridge Crystallographic Data Centre. A range of methodologies was used by the participating groups in order to evaluate the ability of the current computational methods to predict the crystal structures of the six organic molecules chosen as targets for this blind test. The first four targets, two rigid molecules, one semi-flexible molecule and a 1: 1 salt, matched the criteria for the targets from CSP2007, while the last two targets belonged to two new challenging categories - a larger, much more flexible molecule and a hydrate with more than one polymorph. Each group submitted three predictions for each target it attempted. There was at least one successful prediction for each target, and two groups were able to successfully predict the structure of the large flexible molecule as their first place submission. The results show that while not as many groups successfully predicted the structures of the three smallest molecules as in CSP2007, there is now evidence that methodologies such as dispersion-corrected density functional theory (DFT-D) are able to reliably do so. The results also highlight the many challenges posed by more complex systems and show that there are still issues to be overcome
Cross-lingual polarity detection with machine translation
Recent advancements in machine translation foster an interest of its use in sentiment analysis. In this paper, we investigate prospects and limitations of machine translation in sentiment analysis for cross-lingual polarity detection task. We focus on improving classification accuracy in a cross-lingual setting where we have available labeled training instances about particular domain in different languages. We experiment with movie review and product review datasets consisting of polar texts in English and Turkish. The results of the study show that expanding training size with new instances taken from another corpus does not necessarily increase classification accuracy. And this happens primarily not due to (not always accurate) machine translation, but because of the inherent differences in corpora between two subsets written in different languages. Similarly, in case of co-training classification with machine translation we observe from the results that accuracy improvement can be explained by semi-supervised learning with unlabeled data coming from the same domain, but not due to cross-language co-training itself. Our results also show that amount of artificial noise added by machine translation services does not hinder classifiers much in polarity detection task. However, it is important to distinguish the effect of machine translation from the effect of merging different cross-lingual data sources and that like in case of transfer learning we may need to search for ways to account for cross-lingual data distribution differences
Cross-lingual polarity detection with machine translation
Recent advancements in machine translation foster an interest of its use in sentiment analysis. In this paper, we investigate prospects and limitations of machine translation in sentiment analysis for cross-lingual polarity detection task. We focus on improving classification accuracy in a cross-lingual setting where we have available labeled training instances about particular domain in different languages. We experiment with movie review and product review datasets consisting of polar texts in English and Turkish. The results of the study show that expanding training size with new instances taken from another corpus does not necessarily increase classification accuracy. And this happens primarily not due to (not always accurate) machine translation, but because of the inherent differences in corpora between two subsets written in different languages. Similarly, in case of co-training classification with machine translation we observe from the results that accuracy improvement can be explained by semi-supervised learning with unlabeled data coming from the same domain, but not due to cross-language co-training itself. Our results also show that amount of artificial noise added by machine translation services does not hinder classifiers much in polarity detection task. However, it is important to distinguish the effect of machine translation from the effect of merging different cross-lingual data sources and that like in case of transfer learning we may need to search for ways to account for cross-lingual data distribution differences
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