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| 2. |
- Burenhult, Niclas, et al.
(författare)
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Forests : the cross-linguistic perspective
- 2017
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Ingår i: Geographica Helvetica. - : Copernicus GmbH. - 0016-7312 .- 2194-8798. ; 72, s. 455-464
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Tidskriftsartikel (refereegranskat)abstract
- Do all humans perceive, think and talk about tree cover (‘forests’) in more or less the same way? International forestry programs frequently seem to operate on the assumption that they do. However, recent advances in the language sciences show that languages vary greatly as to how the landscape domain is lexicalized and grammaticalized. Different languages segment and label the large-scale environment and its features according to astonishingly different semantic principles, often in tandem with highly culture-specific practices and ideologies. Presumed basic concepts like mountain, valley and river cannot in fact be straightforwardly translated across languages. In this paper we describe, compare and evaluate some of the semantic diversity observed in relation to forests. We do so on the basis of first-hand linguistic field data from a global sample of indigenous categorization systems as they are manifested in the following languages: Avatime (Ghana), Duna (Papua New Guinea), Jahai (Malay Peninsula), Lokono (the Guianas), Makalero (East Timor), and Umpila/Kuuku Ya’u (Cape York Peninsula). We show that basic linguistic categories relating to tree cover vary considerably in their principles of semantic encoding across languages, and that forest is a challenging category from the point of view of inter-cultural translatability. This has consequences for current global policies and programs aimed at standardizing forest definitions and measurements. It calls for greater attention to categorial diversity in designing and implementing such agendas, and for receptiveness to and understanding of local indigenous classification systems in communicating those agendas on the ground.
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| 3. |
- Craddock, Nick, et al.
(författare)
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Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls
- 2010
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 464:7289, s. 713-720
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Tidskriftsartikel (refereegranskat)abstract
- Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to have an important role in genetic susceptibility to common disease. To address this we undertook a large, direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed,19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated similar to 50% of all common CNVs larger than 500 base pairs. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with disease-IRGM for Crohn's disease, HLA for Crohn's disease, rheumatoid arthritis and type 1 diabetes, and TSPAN8 for type 2 diabetes-although in each case the locus had previously been identified in single nucleotide polymorphism (SNP)-based studies, reflecting our observation that most common CNVs that are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs that can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases.
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| 4. |
- Hill, Clair
(författare)
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Expression of the interpersonal connection between narrators and characters in Umpila and Kuuku Ya'u storytelling
- 2016
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Ingår i: Narrative Inquiry. - : John Benjamins Publishing Company. - 1387-6740. ; 26:2, s. 257-285
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Tidskriftsartikel (refereegranskat)abstract
- This article analyses the selection of person reference expressions in narratives in Umpila/Kuuku Ya'u, a Pama-Nyungan language of Cape York Peninsula (Australia). The analysis takes the principle of topic-fittedness, one of a set of design principles proposed to account for the interactional conditioning of person reference formulation, and applies it to Umpila/Kuuku Ya'u narration. The ensuing anlaysis demonstrates that referring practices are conditioned by, and ultimately work to convey, manifold contextual aspects of the narrative and the speech event it is embedded in. The focus is on the narrator's use and manipulation of kin-Terms to highlight the interpersonal connection between themselves and characters. Kin-Term expressions are shown to be fitted to the pragmaticaction being undertaken by the narrator: namely, to signal authority to quote another's words in represented speech; to bolster authority to speak on a subject matter; and to develop a stance in relation to events being narrated.
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| 6. |
- Majid, Asifa, et al.
(författare)
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Differential coding of perception in the world's languages
- 2018
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424. ; 115:45, s. 11369-11376
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Tidskriftsartikel (refereegranskat)abstract
- Is there a universal hierarchy of the senses, such that some senses (e.g., vision) are more accessible to consciousness and linguistic description than others (e.g., smell)? The long-standing presumption in Western thought has been that vision and audition are more objective than the other senses, serving as the basis of knowledge and understanding, whereas touch, taste, and smell are crude and of little value. This predicts that humans ought to be better at communicating about sight and hearing than the other senses, and decades of work based on English and related languages certainly suggests this is true. However, how well does this reflect the diversity of languages and communities worldwide? To test whether there is a universal hierarchy of the senses, stimuli from the five basic senses were used to elicit descriptions in 20 diverse languages, including 3 unrelated sign languages. We found that languages differ fundamentally in which sensory domains they linguistically code systematically, and how they do so. The tendency for better coding in some domains can be explained in part by cultural preoccupations. Although languages seem free to elaborate specific sensory domains, some general tendencies emerge: for example, with some exceptions, smell is poorly coded. The surprise is that, despite the gradual phylogenetic accumulation of the senses, and the imbalances in the neural tissue dedicated to them, no single hierarchy of the senses imposes itself upon language.
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| 7. |
- Romagnoni, A, et al.
(författare)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Tidskriftsartikel (refereegranskat)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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