46 research outputs found
1 Modeling Diverse Standpoints in Text Classification: Learning to Be Human by Modeling Human Values
An annotator’s classification of a text not only tells us something about the intent of the text’s author, it also tells us something about the annotator’s standpoint. To understand authorial intent, we can consider all of these diverse standpoints, as well as the extent to which the annotators ’ standpoints affect their perceptions of authorial intent. To model human behavior, it is important to model humans ’ unique standpoints. Human values play an especially important role in determining human behavior and how people perceive the world around them, so any effort to model human behavior and perception can benefit from an effort to understand and model human values. Instead of training humans to obscure their standpoints and act like computers, we should teach computers to have standpoints of their own
Predicting the impact of scientific concepts using full‐text features
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134425/1/asi23612.pd
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A systems approach using the functional resonance analysis method to support fluoride varnish application for children attending general dental practice
Background
All children attending General Dental Practice in Scotland are recommended to receive twice-yearly applications of sodium fluoride varnish to prevent childhood caries, yet application is variable. Development of complex interventions requires theorizing and modelling to understand context. This study applies the Functional Resonance Analysis Method (FRAM) to produce a sociotechnical systems model and identify opportunities for intervention to support application.
Methods
The FRAM was used to synthesise data which were: routine monitoring of fluoride varnish application in 2015/16; a longitudinal survey with practitioners (n = 1090); in-depth practitioner and key informant interviews (n = 43); and a ‘world café’ workshop (n = 56).
Results
We describe a detailed model of functions linked to application, and use this to make recommendations for system-wide intervention.
Conclusions
Rigorous research is required to produce accessible models of complex systems in healthcare. This novel paper shows how careful articulation of the functions associated with fluoride varnish application can support future improvement efforts
Vocal Interactivity in-and-between Humans, Animals, and Robots
Almost all animals exploit vocal signals for a range of ecologically motivated purposes: detecting predators/prey and marking territory, expressing emotions, establishing social relations, and sharing information. Whether it is a bird raising an alarm, a whale calling to potential partners, a dog responding to human commands, a parent reading a story with a child, or a business-person accessing stock prices using Siri, vocalization provides a valuable communication channel through which behavior may be coordinated and controlled, and information may be distributed and acquired. Indeed, the ubiquity of vocal interaction has led to research across an extremely diverse array of fields, from assessing animal welfare, to understanding the precursors of human language, to developing voice-based human–machine interaction. Opportunities for cross-fertilization between these fields abound; for example, using artificial cognitive agents to investigate contemporary theories of language grounding, using machine learning to analyze different habitats or adding vocal expressivity to the next generation of language-enabled autonomous social agents. However, much of the research is conducted within well-defined disciplinary boundaries, and many fundamental issues remain. This paper attempts to redress the balance by presenting a comparative review of vocal interaction within-and-between humans, animals, and artificial agents (such as robots), and it identifies a rich set of open research questions that may benefit from an interdisciplinary analysis
Combinatoriality in the vocal systems of nonhuman animals
A key challenge in the field of human language evolution is the identification of the selective conditions that gave rise to language's generative nature. Comparative data on nonhuman animals provides a powerful tool to investigate similarities and differences among nonhuman and human communication systems and to reveal convergent evolutionary mechanisms. In this article, we provide an overview of the current evidence for combinatorial structures found in the vocal system of diverse species. We show that considerable structural diversity exits across and within species in the forms of combinatorial structures used. Based on this we suggest that a fine‐grained classification and differentiation of combinatoriality is a useful approach permitting systematic comparisons across animals. Specifically, this will help to identify factors that might promote the emergence of combinatoriality and, crucially, whether differences in combinatorial mechanisms might be driven by variations in social and ecological conditions or cognitive capacities
Genetic Effects at Pleiotropic Loci Are Context-Dependent with Consequences for the Maintenance of Genetic Variation in Populations
Context-dependent genetic effects, including genotype-by-environment and genotype-by-sex interactions, are a potential mechanism by which genetic variation of complex traits is maintained in populations. Pleiotropic genetic effects are also thought to play an important role in evolution, reflecting functional and developmental relationships among traits. We examine context-dependent genetic effects at pleiotropic loci associated with normal variation in multiple metabolic syndrome (MetS) components (obesity, dyslipidemia, and diabetes-related traits). MetS prevalence is increasing in Western societies and, while environmental in origin, presents substantial variation in individual response. We identify 23 pleiotropic MetS quantitative trait loci (QTL) in an F16 advanced intercross between the LG/J and SM/J inbred mouse strains (Wustl:LG,SM-G16; n = 1002). Half of each family was fed a high-fat diet and half fed a low-fat diet; and additive, dominance, and parent-of-origin imprinting genotypic effects were examined in animals partitioned into sex, diet, and sex-by-diet cohorts. We examine the context-dependency of the underlying additive, dominance, and imprinting genetic effects of the traits associated with these pleiotropic QTL. Further, we examine sequence polymorphisms (SNPs) between LG/J and SM/J as well as differential expression of positional candidate genes in these regions. We show that genetic associations are different in different sex, diet, and sex-by-diet settings. We also show that over- or underdominance and ecological cross-over interactions for single phenotypes may not be common, however multidimensional synthetic phenotypes at loci with pleiotropic effects can produce situations that favor the maintenance of genetic variation in populations. Our findings have important implications for evolution and the notion of personalized medicine
HIV-1 drug resistance mutations emerging on darunavir therapy in PI-naive and -experienced patients in the UK
\ua9 The Author 2016. Background: Darunavir is considered to have a high genetic barrier to resistance. Most darunavir-associated drug resistance mutations (DRMs) have been identified through correlation of baseline genotype with virological response in clinical trials. However, there is little information on DRMs that are directly selected by darunavir in clinical settings. Objectives: We examined darunavir DRMs emerging in clinical practice in the UK. Patients and methods: Baseline and post-exposure protease genotypes were compared for individuals in the UK Collaborative HIV Cohort Study who had received darunavir; analyses were stratified for PI history. A selection analysis was used to compare the evolution of subtype B proteases in darunavir recipients and matched PInaive controls. Results: Of 6918 people who had received darunavir, 386 had resistance tests pre- and post-exposure. Overall, 2.8% (11/386) of these participants developed emergent darunavir DRMs. The prevalence of baseline DRMs was 1.0% (2/198) among PI-naive participants and 13.8% (26/188) among PI-experienced participants. Emergent DRMs developed in 2.0% of the PI-naive group (4 mutations) and 3.7% of the PI-experienced group (12 mutations). Codon 77 was positively selected in the PI-naive darunavir cases, but not in the control group. Conclusions: Our findings suggest that although emergent darunavir resistance is rare, it may be more common among PI-experienced patients than those who are PI-naive. Further investigation is required to explore whether codon 77 is a novel site involved in darunavir susceptibility
Virological failure and development of new resistance mutations according to CD4 count at combination antiretroviral therapy initiation
Objectives: No randomized controlled trials have yet reported an individual patient benefit of initiating combination antiretroviral therapy (cART) at CD4 counts > 350 cells/μL. It is hypothesized that earlier initiation of cART in asymptomatic and otherwise healthy individuals may lead to poorer adherence and subsequently higher rates of resistance development. Methods: In a large cohort of HIV-positive individuals, we investigated the emergence of new resistance mutations upon virological treatment failure according to the CD4 count at the initiation of cART. Results: Of 7918 included individuals, 6514 (82.3%), 996 (12.6%) and 408 (5.2%) started cART with a CD4 count ≤ 350, 351-499 and ≥ 500 cells/μL, respectively. Virological rebound occurred while on cART in 488 (7.5%), 46 (4.6%) and 30 (7.4%) with a baseline CD4 count ≤ 350, 351-499 and ≥ 500 cells/μL, respectively. Only four (13.0%) individuals with a baseline CD4 count > 350 cells/μL in receipt of a resistance test at viral load rebound were found to have developed new resistance mutations. This compared to 107 (41.2%) of those with virological failure who had initiated cART with a CD4 count < 350 cells/μL. Conclusions: We found no evidence of increased rates of resistance development when cART was initiated at CD4 counts above 350 cells/μL. HIV Medicin