Overtly/Non-Overtly Inflected Infinitives in Romance

info:eu-repo/semantics/publishedVersio

How much syntax is there in Metalinguistic Negation?

This paper explores the syntax of unambiguous metalinguistic negation (MN) markers in European Portuguese (EP) with the main goal of demonstrating the syntactic import of MN. Taking the EP facts as a means to gain insight into the grammatical encoding of MN in natural language, the paper shows that unambiguous MN markers split into two types: peripheral and internal. This split is confirmed by their contrasting behavior with respect to different syntactic tests, e.g.: availability in isolation and nominal fragments; ability to take scope over negation and emphatic/contrastive high constituents; compatibility with VP Ellipsis. Peripheral MN markers respond positively to all the tests, whereas internal ones respond negatively. These facts are derived from a syntactic analysis where CP plays a central and unifying role. It is proposed that while the cross-linguistically pervasive peripheral MN markers directly merge into Spec,CP, the more unusual sentence-internal MN markers are rooted in the TP domain and reach Spec,CP by movement. The centrality of the CP field is motivated by elaborating on Farkas and Bruce’s (2010) model of polarity features. Under the hypothesis that besides the relative polarity features [same] and [reverse], there is a feature [objection] that singles out MN declaratives among responding assertions, this is taken to be the edge feature that drives unambiguous MN markers into the CP space.info:eu-repo/semantics/publishedVersio

Household composition after resettlement and emotional health in adolescent migrants

BACKGROUND: Migration during adolescence constitutes an important stressor that particularly impacts unaccompanied minors (UAM). Adolescent UAM in the United States (U.S.) are relatively understudied, especially regarding their resilience and emotional well-being after resettlement. Small school-based studies have documented the mental health status of UAM who resettled reuniting with their parents. However, many do not resettle with parents and less is known about the degree to which post-resettlement household composition impacts resilience and emotional well-being. METHODS: Our goal was to examine how migration characteristics, supports, resilience, and emotional well-being vary by UAM resettlement household composition (reunification with parents, reunification with a non-parental family member, or living in a household not containing any family members). Using a mixed-methods (quantitative-qualitative) cross-sectional approach, we assessed 46 Latin American adolescent UAM to the U.S. who resettled into these three household types. RESULTS: Youth experienced support differently by household type, influencing their strategies for adapting and coping post-resettlement, impacting their resilience (Kruskal Wallis-H 4.8; p<0.09) and emotional well-being (Kruskal Wallis 5.3; p<0.07). Youth living in households without relatives (n = 9) had lower resilience (Fisher's exact test p<0.002) and positive affect (Fisher's exact test p<0.003) and needed to expend greater efforts to mobilize social supports than youth living with parents (n = 22) or with non-parental family members (n = 15). CONCLUSION: The needs and coping abilities of UAM migrants vary with the composition of their immediate receiving environment, their post-resettlement household. Understanding differences associated with these household characteristics can guide interventions to maximize emotional health and resilience

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.