Trauma-Informed Care (TIC) Interventions: An Evidence-Based Practice Project

This Evidence-Based Practice (EBP) project examined the following question: What are the characteristics and effectiveness of trauma-informed care (TIC) approaches on health and participation (well-being, quality of life) outcomes for populations who have experienced trauma

Improving the use of crop models for risk assessment and climate change adaptation

Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1. Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk? 2. Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output. 3. Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper

An empirical study of the effect of acoustic-prosodic entrainment on the perceived trustworthiness of conversational avatars

Entrainment is the tendency of interlocutors to become more similar to each other in their way of speaking. This phenomenon has been repeatedly documented and is associated with multiple social aspects of human-human conversations. However, there is a dearth of research on the effects of spoken dialogue systems (SDSs) with implemented acoustic-prosodic (dis)entrainment policies. The goal of the present work is to provide further empirical evidence on how acoustic-prosodic (dis)entraining policies affect users. In particular, this article focuses on its effects on users’ trust toward the SDSs. In the experiments reported here we analyze if and how different acoustic-prosodic (dis)entrainment policies affect users’ perception of a system's ability. We collected data from 98 unique participants, all native speakers of Argentine Spanish. Our results suggest that acoustic-prosodic (dis)entrainment in spoken dialogue systems is effectively associated with the way users perceive the capabilities of such systems. Characterizing these effects remains a challenging task. Overall, we observe a positive effect on trust of entrainment on intensity and a negative effect of entrainment on pitch. Estimated effect sizes are far from negligible.Fil: Gálvez, Ramiro Heraclio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Gravano, Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Beňuš, Štefan. Constantine the Philosopher University in Nitra; Eslovaquia. Slovak Academy Of Sciences. Institute Of Informatics; EslovaquiaFil: Levitan, Rivka. Brooklyn College ; City University Of New York;Fil: Trnka, Marian. Slovak Academy Of Sciences. Institute Of Informatics; EslovaquiaFil: Hirschberg, Julia. Columbia University; Estados Unido

SARS-CoV-2 nucleocapsid protein forms condensates with viral genomic RNA.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes COVID-19, a pandemic that seriously threatens global health. SARS-CoV-2 propagates by packaging its RNA genome into membrane enclosures in host cells. The packaging of the viral genome into the nascent virion is mediated by the nucleocapsid (N) protein, but the underlying mechanism remains unclear. Here, we show that the N protein forms biomolecular condensates with viral genomic RNA both in vitro and in mammalian cells. Phase separation is driven, in part, by hydrophobic and electrostatic interactions. While the N protein forms spherical assemblies with unstructured RNA, it forms asymmetric condensates with viral RNA strands that contain secondary structure elements. Cross-linking mass spectrometry identified a region that forms interactions between N proteins in condensates, and truncation of this region disrupts phase separation. We also identified small molecules that alter the formation of N protein condensates. These results suggest that the N protein may utilize biomolecular condensation to package the SARS-CoV-2 RNA genome into a viral particle