1,161 research outputs found
An automatic adaptive method to combine summary statistics in approximate Bayesian computation
To infer the parameters of mechanistic models with intractable likelihoods,
techniques such as approximate Bayesian computation (ABC) are increasingly
being adopted. One of the main disadvantages of ABC in practical situations,
however, is that parameter inference must generally rely on summary statistics
of the data. This is particularly the case for problems involving
high-dimensional data, such as biological imaging experiments. However, some
summary statistics contain more information about parameters of interest than
others, and it is not always clear how to weight their contributions within the
ABC framework. We address this problem by developing an automatic, adaptive
algorithm that chooses weights for each summary statistic. Our algorithm aims
to maximize the distance between the prior and the approximate posterior by
automatically adapting the weights within the ABC distance function.
Computationally, we use a nearest neighbour estimator of the distance between
distributions. We justify the algorithm theoretically based on properties of
the nearest neighbour distance estimator. To demonstrate the effectiveness of
our algorithm, we apply it to a variety of test problems, including several
stochastic models of biochemical reaction networks, and a spatial model of
diffusion, and compare our results with existing algorithms
A comparison of the results from intra-pleural and intra-peritoneal studies with those from inhalation and intratracheal tests for the assessment of pulmonary responses to inhalable dusts and fibres.
The aim of this paper is to compare results from inhalation studies with those from intraperitoneal and intrapleural tests, where available, for a number of fibrous and particulate test materials. The objective is to determine how well intraperitoneal/intrapleural studies predict the pathological responses observed in more standard in vivo studies of pulmonary toxicity, with a particular focus on carcinogenicity. Published toxicity data was obtained for a number of materials including asbestos, wollastonite, MMVFs (including glass fibres, stone wools and RCF), silicon carbide whiskers, potassium octatitanate, quartz, kevlar, polypropylene and titanium dioxide. For some of the fibrous material reviewed, there is conformity between the results of intraperitoneal and inhalation tests such that they are either consistently positive or consistently negative. For the remaining fibrous materials reviewed, intraperitoneal and inhalation tests give different results, with positive results in the intraperitoneal test not being reflected by positive inhalation results. It is suggested that the intraperitoneal test can be used to exonerate a dust or fibre (because if negative in the intraperitoneal test it is extremely unlikely to be positive in either inhalation or intratracheal tests) but should not be used to positively determine that a dust or fibre is carcinogenic by inhalation. We would argue against the use of intraperitoneal tests for human health risk assessment except perhaps for the purpose of exoneration of a material from classification as a carcinogen.Peer reviewedFinal Accepted Versio
The impact of temporal sampling resolution on parameter inference for biological transport models
Imaging data has become widely available to study biological systems at
various scales, for example the motile behaviour of bacteria or the transport
of mRNA, and it has the potential to transform our understanding of key
transport mechanisms. Often these imaging studies require us to compare
biological species or mutants, and to do this we need to quantitatively
characterise their behaviour. Mathematical models offer a quantitative
description of a system that enables us to perform this comparison, but to
relate these mechanistic mathematical models to imaging data, we need to
estimate the parameters of the models. In this work, we study the impact of
collecting data at different temporal resolutions on parameter inference for
biological transport models by performing exact inference for simple velocity
jump process models in a Bayesian framework. This issue is prominent in a host
of studies because the majority of imaging technologies place constraints on
the frequency with which images can be collected, and the discrete nature of
observations can introduce errors into parameter estimates. In this work, we
avoid such errors by formulating the velocity jump process model within a
hidden states framework. This allows us to obtain estimates of the
reorientation rate and noise amplitude for noisy observations of a simple
velocity jump process. We demonstrate the sensitivity of these estimates to
temporal variations in the sampling resolution and extent of measurement noise.
We use our methodology to provide experimental guidelines for researchers
aiming to characterise motile behaviour that can be described by a velocity
jump process. In particular, we consider how experimental constraints resulting
in a trade-off between temporal sampling resolution and observation noise may
affect parameter estimates.Comment: Published in PLOS Computational Biolog
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SERVICE PROVIDERS PERSPECTIVE ON THE UNIQUE NEEDS OF SEXUALLY EXPLOITED WOMEN AND CHILDREN IN THE INLAND EMPIRE
The purpose of this qualitative research study was to explore and expose the needs of sexually exploited women and children. The participants were recruited from a few non-profit agencies in the Inland Empire area. This study found one of the most underlying challenge facing the participants when working with sexually exploited victims was the unavailability of resources, particularly, shortage of transitional housing for them. Another finding that featured prominently in the study was related to a need for continuous training and education for the service providers in order to stay current with trends. The study also identified the rapport building challenges faced by service providers and the risk of re-traumatization for these victims and proper types of treatment for these individuals.
This study recommends that the policymakers work with other key stakeholders to provide resources to these service providers in addition to providing a favorable environment. The collaboration should also include the law enforcement agencies and the judicial officers to protect the victims from further suffering. Furthermore, the study suggests that attention should be placed on the development of awareness campaigns and stronger voices of support and advocacy for these victims
Wit, witticisms and humor of Plautus
Thesis (M.A.)--University of Illinois, 1909.Typescript.Includes bibliographical references (leaf [1] at end)
EXPLORING THE USE OF THE CRITICAL INCIDENT AS A WAY OF ENCOURAGING REFLECTIVE PRACTICE IN PROFESSIONAL LEARNING SETTINGS
This study examines the use by student teachers and their supervising senior teachers in partner secondary schools of critical incident analysis, as part of a required directed task for all student teachers on the one-year postgraduate education course at Leicester. Systematic analysis using evidence from students’ reflective writing about critical incidents, and one-to-one interview data, was carried out at the mid-point and end of year. Critical moments and their analysis emerge as professional ‘turning points’ for many student teachers. This is particularly so when professional learning conversations in relation to the critical incident also take place. Individuals’ choices of different writing structures as scaffolding devices for supporting the narratives and their analysis indicate high levels of personalization in learning. As an outcome, more structured support has been developed for many of the supervising teachers to raise their awareness of the importance of, and their skills within, professional dialogues, in order to enhance and deepen reflective practice.A ‘Reflection Framework’ used in the analysis of the written narratives shows considerable potential for further academic work in finding ways of supporting understanding of deeper reflective practice, which should be of interest in a variety of professional and vocational settings
Evaluation of outreach interventions for under 16 year olds. Tools and guidance for higher education providers
During 2017-18, OFFA commissioned research that aimed to understand the nature of outreach activities for under 16 year olds (which were funded through access and participation investment) and how these were evaluated. This document, developed from the research, is intended to act as a resource for pre-16 outreach practitioners and evaluators, drawing both on the data collected by this project and the wider literature around evaluation and outreach. It seeks to recognise the complexity of pre-16 outreach work and eschews a prescriptive approach in favour of establishing important principles and actions that are likely to underpin good practice. Our discussion is broadly positioned within a ‘social realist’ worldview (Archer, 2008; Pawson, 2013) that seeks to understand the fuzzy nature of the cause-and-effect relationships that exist within complex social fields, where individuals construct their own realities in reference to those around them. There is a particular focus on epistemology – the pathways to creating dependable, if contingent, knowledge – as a vehicle for making meaning from data that is usually incomplete, compromised or mediated through young people’s emergent constructions of their worlds. Fundamentally, outreach is predicated on the ability of practitioners to influence young people in a planned way, albeit that the plan will not always work for every young person in every cohort. An important element in this epistemology is that it is not concerned with finding single ‘solutions’ that exist outside time and context. Rather, it is concerned with understanding how young people are influenced by their life experiences – not ‘what works’, but what works in a given context and, importantly, why. It is only through understanding the latter element that practices can become robustly effective in the long-term and potentially transferable to other contexts. This is particularly appropriate to pre-16 outreach work due to the lengthy time lag between activity and application to higher education (HE).Office for Students (OfS
Understanding the evaluation of access and participation outreach interventions for under 16 year olds
The project team was asked to address the following six research questions and these were used to guide the project: 1. What are the intended outcomes for current outreach interventions directed at under 16 year olds from disadvantaged backgrounds where the long-term aim is to widen access to higher education (HE)? 2. What types of outreach intervention activity or activities are institutions using in relation to intended outcomes? 3. What evaluation tools, methods and metrics are being used to measure the intended outcomes? 4. What are the perceived and actual challenges and barriers for different stakeholders to effective evaluation of long-term outreach? 5. What do different stakeholders consider most effective evaluation practice and why? 6. How valid and suitable are the evaluation tools, methods and metrics (identified through the research) that are commonly used? The project was constructed around six interlinked work packages: 1. A quantitative analysis of what higher education providers (HEPs) say about their pre-16 outreach activities (and their evaluation) in their 2017-18 access agreements (as the most recent available). 2. An online survey of HEPs to gather information about the pre-16 outreach activities delivered during the 2016-17 academic year and their evaluation, as well as the structure of their evaluation resources and challenges faced. 3. Case studies of four HEPs identified as demonstrating elements of good practice through their access agreements and the online survey, derived from telephone interviews with key staff and documentary analysis. 4. Telephone interviews with 11 third sector organisations (TSOs) to explore their practices and the evaluation of their activities, providing a counterpoint to the data collected from higher education institutions (HEIs). 5. A synthesis of the four preceding work packages to explore elements of good practice, determine a basis for assessing the quality of evaluations and highlight challenges for the sector and OFFA. 6. An invited participatory workshop for evaluators from HEPs and TSOs identified as demonstrating elements of good practice through the online survey and telephone interviews, to act as a sounding board for the emerging conclusions and recommendations.Office for Students (OfS
An automatic adaptive method to combine summary statistics in approximate Bayesian computation
To infer the parameters of mechanistic models with intractable likelihoods, techniques such as approximate Bayesian computation (ABC) are increasingly being adopted. One of the main disadvantages of ABC in practical situations, however, is that parameter inference must generally rely on summary statistics of the data. This is particularly the case for problems involving high-dimensional data, such as biological imaging experiments. However, some summary statistics contain more information about parameters of interest than others, and it is not always clear how to weight their contributions within the ABC framework. We address this problem by developing an automatic, adaptive algorithm that chooses weights for each summary statistic. Our algorithm aims to maximize the distance between the prior and the approximate posterior by automatically adapting the weights within the ABC distance function. Computationally, we use a nearest neighbour estimator of the distance between distributions. We justify the algorithm theoretically based on properties of the nearest neighbour distance estimator. To demonstrate the effectiveness of our algorithm, we apply it to a variety of test problems, including several stochastic models of biochemical reaction networks, and a spatial model of diffusion, and compare our results with existing algorithms
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Are you in or are you out? The importance of group saliency in own-group biases in face recognition
Previous research has demonstrated several own-group biases (OGBs) in face recognition, but why they occur is unclear. Social–cognitive accounts suggest they stem from differential attention and facial processing, following the categorisation of a face as belonging to an “in” or “out” group. Three studies explored whether OGBs can be produced by mere categorisation at encoding and investigated the role of in-group membership saliency on face recognition. Participants saw 40 facial images fictionally grouped according to in-/out-group status. Studies 1 and 2 used university membership as the grouping variable and found no evidence of an OGB, and no relationship between OGB magnitude and salience of group membership. Study 3 used the same design as Study 2, but with a highly salient group characteristic: participants’ stance on the U.K. Referendum (i.e., whether they were “Leave” or “Remain” supporters). In this case, an asymmetrical OGB was found, with only Remain voters demonstrating an OGB. Furthermore, a relationship between OGB magnitude and attitude toward the Referendum result was found. Overall, our results suggest that social categorisation and membership saliency alone may not be enough to moderate in- and out-group face recognition. However, when sufficiently polarised groups are used as in-/out-group categories, OGBs may occur
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