The role of external factors on the reactivation of the heritage language of Turkish-German returnees.

Introduction: This study investigates the heritage language performance of Turkish-German returnees upon their reintegration into Turkey and explores the impact of external factors on their proficiency in the (re-)activated heritage language (HL). Methods: Data collection involved the participation of 28 Turkish heritage speakers and a control group of 28 monolingual speakers. The language proficiency of both groups was assessed through a cloze test and an error correction task with a focus on converbial constructions, evidentiality and direct object case marking in Turkish. A sociolinguistic background questionnaire was used to obtain information about their language experiences. The study focused on understanding the individual and group differences in returnee's heritage language performance. Additionally, random forest analysis was employed to investigate the relative influence of external factors on individual variability within the returnee group. Results and Discussion: The analysis of results revealed notable group differences between the returnees and the control group, emphasizing the unique linguistic challenges faced by those who returned to Turkey. Within the returnee group, there was considerable individual variability in heritage language performance. The subsequent exploration of individual variation highlighted the significant role of external factors. Notably, the length of residence in Germany, the age at which participants returned to Turkey, and the frequency of Turkish language use in their migration context emerged as significant predictors of the returnee participants' proficiency in their (re-)activated HL. Surprisingly, formal contact with the dominant German language did not exert a substantial impact on the returnees' language proficiency, suggesting the nuanced influence of various external factors on heritage language development.

Documenting heritage language experience using questionnaires.

Introduction: There exists a great degree of variability in the documentation of multilingual experience across different instruments. The present paper contributes to the "methods turn" and individual differences focus in (heritage) bilingualism by proposing a comprehensive online questionnaire building on existing questionnaires and the experience of using them to document heritage bilingualism: the Heritage Language Experience (HeLEx) online questionnaire. HeLEx is validated against and contrasted to an extended version of the Language and Social Background Questionnaire designed for heritage speakers (HSs), LSBQ-H. Methods: We compare data elicited with both questionnaires in turn from a group of Turkish HSs (n = 174, mean age=32). Our validation focuses on traditional language background variables, including language exposure and use, language proficiency, language dominance, as well as a more novel measure of language entropy. The analyses are based on a subset of key questions from each questionnaire that capture language experience for up to five languages, four modalities, and five social contexts. In a subsequent set of analyses, we explore the impact of different types of response scales, response mechanisms, and manners of variable derivation on the informativity of the data they can provide, in terms of the scope, granularity and distributional properties of the derived measures. Results and Discussion: Our results show that both HeLEx and LSBQ-H are successful at detecting the important distributional patterns in the data and reveal a number of advantages of HeLEx. In the discussion, we consider the impact of methodological choices regarding question phrasing, visual format, response options, and response mechanisms. We emphasize that these choices are not trivial and can affect the derived measures and subsequent analyses on the impact of individual differences on language acquisition and processing.

COVID-19 detection on chest radiographs using feature fusion based deep learning.

The year 2020 will certainly be remembered in human history as the year in which humans faced a global pandemic that drastically affected every living soul on planet earth. The COVID-19 pandemic certainly had a massive impact on human's social and daily lives. The economy and relations of all countries were also radically impacted. Due to such unexpected situations, healthcare systems either collapsed or failed under colossal pressure to cope with the overwhelming numbers of patients arriving at emergency rooms and intensive care units. The COVID -19 tests used for diagnosis were expensive, slow, and gave indecisive results. Unfortunately, such a hindered diagnosis of the infection prevented abrupt isolation of the infected people which, in turn, caused the rapid spread of the virus. In this paper, we proposed the use of cost-effective X-ray images in diagnosing COVID-19 patients. Compared to other imaging modalities, X-ray imaging is available in most healthcare units. Deep learning was used for feature extraction and classification by implementing a multi-stream convolutional neural network model. The model extracts and concatenates features from its three inputs, namely; grayscale, local binary patterns, and histograms of oriented gradients images. Extensive experiments using fivefold cross-validation were carried out on a publicly available X-ray database with 3886 images of three classes. Obtained results outperform the results of other algorithms with an accuracy of 97.76%. The results also show that the proposed model can make a significant contribution to the rapidly increasing workload in health systems with an artificial intelligence-based automatic diagnosis tool.

Language Dominance Affects Bilingual Performance and Processing Outcomes in Adulthood.

This study examines the role of language dominance (LD) on linguistic competence outcomes in two types of early bilinguals: (i) child L2 learners of Catalan (L1 Spanish-L2 Catalan and, (ii) child Spanish L2 learners (L1 Catalan-L2 Spanish). Most child L2 studies typically focus on the development of the languages during childhood and either focus on L1 development or L2 development. Typically, these child L2 learners are immersed in the second language. We capitalize on the unique situation in Catalonia, testing the Spanish and Catalan of both sets of bilinguals, where dominance in either Spanish or Catalan is possible. We examine the co-occurrence of Sentential Negation (SN) with a Negative Concord Item (NCI) in pre-verbal position (Catalan only) and Differential Object Marking (DOM) (Spanish only). The results show that remaining dominant in the L1 contributes to the maintenance of target-like behavior in the language.