A detection theory account of change detection

Previous studies have suggested that visual short-term memory (VSTM) has a storage limit of approximately four items. However, the type of high-threshold (HT) model used to derive this estimate is based on a number of assumptions that have been criticized in other experimental paradigms (e.g., visual search). Here we report findings from nine experiments in which VSTM for color, spatial frequency, and orientation was modeled using a signal detection theory (SDT) approach. In Experiments 1-6, two arrays composed of multiple stimulus elements were presented for 100 ms with a 1500 ms ISI. Observers were asked to report in a yes/no fashion whether there was any difference between the first and second arrays, and to rate their confidence in their response on a 1-4 scale. In Experiments 1-3, only one stimulus element difference could occur (T = 1) while set size was varied. In Experiments 4-6, set size was fixed while the number of stimuli that might change was varied (T = 1, 2, 3, and 4). Three general models were tested against the receiver operating characteristics generated by the six experiments. In addition to the HT model, two SDT models were tried: one assuming summation of signals prior to a decision, the other using a max rule. In Experiments 7-9, observers were asked to directly report the relevant feature attribute of a stimulus presented 1500 ms previously, from an array of varying set size. Overall, the results suggest that observers encode stimuli independently and in parallel, and that performance is limited by internal noise, which is a function of set size

Adapting to change: Time for climate resilience and a new adaptation strategy. EPC Issue Paper 5 March 2020

The dramatic effects of climate change are being felt across the European continent and the world. Considering how sluggish and unsuccessful the world has been in reducing greenhouse gas (GHG) emissions, the impacts will become long-lasting scars. Even implementing radical climate mitigation now would be insufficient in addressing the economic, societal and environmental implications of climate change, which are expected to only intensify in the years to come. This means climate mitigation must go hand in hand with the adaptation efforts recognised in the Paris Agreement. And although the damages of climate change are usually localised and adaptation measures often depend on local specificities, given the interconnections between ecosystems, people and economies in a globalised world there are strong reasons for European Union (EU) member states to join forces, pool risk and cooperate across borders. Sharing information, good practices, experiences and resources to strengthen resilience and enhance adaptive capacity makes sense economically, environmentally and socially. The European Commission’s 2013 Adaptation Strategy is the first attempt to set EU-wide adaptation and climate resilience and could be considered novel in that it tried to mainstream adaptation goals into relevant legislation, instruments and funds. It was not very proactive, however. It also lacked long-term perspective, failed to put the adaptation file high on the political agenda, was under resourced, and suffered from knowledge gaps and silo thinking. The Commission’s European Green Deal proposal, which has been presented as a major step forward to the goal of Europe becoming the world’s first climate-neutral continent, suggests that the Commission will adopt a new EU strategy on adaptation to climate within the first two years of its mandate (2020-2021). In light of the risks climate change poses to ecosystems, societies and the economy (through inter alia the vulnerability of the supply chain to climate change and its potential failure to provide services to consumers), adaptation should take a prominent role alongside mitigation in the EU’s political climate agenda. Respecting the division of treaty competences, there are important areas where EU-wide action and support could foster the continent’s resilience to climate change. The European Policy Centre (EPC) project “Building a climate-resilient Europe”, which has culminated in this Issue Paper, has identified the following: (i) the ability to convert science-based knowledge into preventive action and responsible behaviour, thus filling the information gap; (ii) the need to close the protection gap through better risk management and risk sharing; (iii) the necessity to adopt nature-based infrastructural solutions widely and tackle the grey infrastructure bias; and (iv) the need to address the funding and investment gap. This Issue Paper aims to help inform the upcoming EU Adaptation Strategy and, by extension, strengthen the EU’s resilience to climate change. To that end, the authors make a call for the EU to mainstream adaptation and shift its focus from reacting to disasters to a more proactive approach that prioritises prevention, risk reduction and resilience building. In doing so, the EU must ensure fairness and distributive justice while striving for climate change mitigation and protecting the environment and biodiversity. To succeed, the new EU Adaptation Strategy will need to address specific challenges related to the information, protection, funding and investment gaps; and the grey infrastructure bias. To tackle and address those challenges, this Paper proposes 17 solutions outlined in Table 1 (see page 6)

Assessing the payback from health R & D: From ad hoc studies to regular monitoring

Chapter 1 : Introduction • The increasing demands for the benefits of payback from publicly funded R&D to be assessed are based partly on the need to justify or account for expenditure on R&D, and partly on the desire for information to assist resource allocation and the better management of R&D funds. The former consideration is particularly strong in relation to the R&D expenditure that comes out of the wider NHS budget. • In this report a range of categories of payback will be identified along with a variety of methods for assessing them. • The aim of the report is to make recommendations as to how the outcomes from health research might best be monitored on a regular basis. The specific context of the report is the NHS R&D Programme but many of the issues will be relevant for a wide range of funders of health R&D. • The introduction sets out not only a plan of the report but also suggests that readers familiar with the general arguments and existing literature may choose to jump to Chapter 6. Chapter 2 : Review of Existing Approaches to Assessing the Payback from Research • Existing work describes various approaches to valuing research. Some are ex ante and attempt to predict the outcomes of research being considered, others are ex post or retrospective. • The five categories of benefit or payback from health R&D that have been identified involve contributions: to knowledge; to research capacity and future research; to improved information for decision making; to the efficiency, efficacy and equity of health care services; and to the nation’s economic performance. These are shown in Table 1 of the report • The process by which R&D generates final outcomes can be modelled as a sequence. This includes primary outputs such as publications; secondary outputs in the form of policy or administrative decisions; and final outcomes which comprise the health and economic benefits. Feedback loops are also introduced and mitigate the limitations of a linear approach. • Qualitative and quantitative approaches can be used but there are immense problems with time lags and attributing outcomes, and sometimes even outputs, to specific items of research funding. • Four common methods of measuring payback can be used. Expert review, by peers or, sometimes, users is the traditional way of assessing the quality of research. Bibliometric techniques can involve not only counting publications but also using datasets such as the Science Citation Index and Wellcome’s Research Outputs Database (ROD). The various methods of economic analysis of payback are difficult to undertake given the costs and problems of acquiring relevant information and estimating benefits. Social science methods include case studies, which can provide useful information but are resource intensive, and questionnaires to researchers and potential research users. Chapter 3 : Characteristics of a Routine Monitoring System • In moving from ad hoc or research studies of payback towards a more regular monitoring it is noted that whereas there has always been a tradition of evaluation of research, in the public services in general there is now a greater emphasis on audit and performance measurement and indicators. A review of these various systems suggests we should be looking to develop a system of outcomes monitoring that incorporates performance indicators (PIs) and measurement rather than an audit system that is trying to monitor activities against predetermined targets. • Standard characteristics of performance measurement systems do not necessarily apply to research where, for example, there are non-standard outputs. Difficulties have arisen in the USA in attempting to apply the Government Performance and Results Act to research funding agencies. It is shown that because the findings of basic research, in particular, enter a knowledge pool in which people and ideas interact, it is difficult to use a PIs’ approach to track eventual outcomes. However, for some types of health research it has proved more feasible to trace the flow between research outputs and outcomes. • An outcomes monitoring system could be useful if it met the following criteria: relevant to, with as comprehensive coverage as possible of, the funders objectives; relevant to the funder’s decision making processes; encourages accurate compliance; minimises unintended consequences; and has acceptable costs. Chapter 4 : Differences Between Research Types • The range of differences between types of research can be relevant for the design of a routine monitoring system. The OECD distinguishes between basic research, applied research and experimental development. Most DH/NHS research is applied. There might be more of a tradition of publication of findings in applied research in health than in other fields. Nevertheless, the publication and incentives patterns operating in basic research mean that it would be inappropriate to use bibliometric indicators in a simple way across all fields even in health research. • Despite having some differences from health research in publication patterns and in the detailed categories of payback, the broad approach proposed in Chapter 6 could be applied to social care research. • Research that is commissioned, especially by the government, has some of the minimum conditions built into it that are associated with outcomes being generated, in particular because the funder has identified that a contribution in this area will be valuable. Chapter 5 : What Units of Research? • The term programme has various meanings including being used to describe a collection of projects on a common theme and to describe a block of funding for a research unit. • Three main streams or modes of funding can be identified: projects, which are administratively grouped into programmes including a responsive programme; institutions/centres/units; individual researchers. These 3 streams are displayed in Figure 1. It is probable that the regular data-gathering for a monitoring system would operate at the basic level of each stream or mode. • Previous work demonstrates that the full range of benefits can sometimes be applied at the level of projects, either in the responsive mode or in programmes, through the use of questionnaires to researchers. Expert and user review and user surveys have also been applied. • Institutions and centres increasingly have experience not only of traditional periodic expert review but also of producing annual reports, although there are debates about what dimensions to include in such reviews and reports. • Individuals in receipt of research development awards have completed questionnaires during and after the awards. These concentrate on the development of research capacity but can go wider. Chapter 6 : A Possible Comprehensive Outcomes Monitoring System • The proposed system is intended for DH/NHS to monitor the outcomes from its R&D in order to justify the R&D expenditure and assist with managing the portfolio. More detailed information is required for the latter purpose. • We propose a multidimensional approach be adopted to cover all the dimensions of payback and that information be gathered from three sets of sources and Table 3 shows which methods would cover which output/outcome categories. • Firstly, possibly annually, a questionnaire (possibly electronic) covering most payback categories should gather data from the basic level of each funding stream ie. from lead researchers of projects, from research institutions/centres, and from individual award holders. • Secondly, supplementary information should be gathered from external databases (including the citation indices and Wellcome’s ROD). • Thirdly, a range of approaches ie. user surveys, reviews by experts and peers, case studies including economic evaluations, and analysis of sources used in policy documents such as NICE guidelines, would be undertaken on a sample basis. They would provide not only supplementary information but, as with the external databases, would also verify the data collected directly from researchers. • These proposals can be evaluated against the criteria set out in Chapter 3: • The system is relevant to DH’s objectives of generating payback in a range of categories. • Various problems have to be overcome before the system could be fully decision relevant. Firstly it might be necessary to ask researchers to apportion the contribution made to specific outputs from various funding streams. Second, to be decision relevant the information would have to be analysed and presented in a manner consistent with funders’ decision making processes. This would involve a) showing how for each outcome and output, for example publications, data from one project or stream could be compared with those from another and b) demonstrating how different outputs and outcomes could be aggregated. • The questions of accuracy of data, minimisation of unintended consequences and the acceptability of the net costs are also addressed. Chapter 7 : Research and Monitoring • Whilst this report is primarily concerned with moving from ad hoc studies towards a routine monitoring system there are issues that need further research. • Before embarking on full implementation the feasibility needs to be tested of items such as on-line recording of data and asking researchers to attribute proportions of research outputs to separate funding agencies. • Once the system is implemented the value of some items can be better assessed, for example the additional value provided by self reporting of publications beyond that gained from relying on external databases. • The data provided by the system would provide opportunities for further payback research on, for example, links between publications and other categories of payback. • Some items such as network analysis could potentially be added to the monitoring system after further examination of them. • Finally the benefit from the monitoring system itself should be assessed.Department of Health; Wellcome Trus

The envirome and the connectome: exploring the structural noise in the human brain associated with socioeconomic deprivation

Complex cognitive functions are widely recognized to be the result of a number of brain regions working together as large-scale networks. Recently, complex network analysis has been used to characterize various structural properties of the large scale network organization of the brain. For example, the human brain has been found to have a modular architecture i.e. regions within the network form communities (modules) with more connections between regions within the community compared to regions outside it. The aim of this study was to examine the modular and overlapping modular architecture of the brain networks using complex network analysis. We also examined the association between neighborhood level deprivation and brain network structure – modularity and grey nodes. We compared network structure derived from anatomical MRI scans of 42 middle-aged neurologically healthy men from the least (LD) and the most deprived (MD) neighborhoods of Glasgow with their corresponding random networks. Cortical morphological covariance networks were constructed from the cortical thickness derived from the MRI scans of the brain. For a given modularity threshold, networks derived from the MD group showed similar number of modules compared to their corresponding random networks, while networks derived from the LD group had more modules compared to their corresponding random networks. The MD group also had fewer grey nodes – a measure of overlapping modular structure. These results suggest that apparent structural difference in brain networks may be driven by differences in cortical thicknesses between groups. This demonstrates a structural organization that is consistent with a system that is less robust and less efficient in information processing. These findings provide some evidence of the relationship between socioeconomic deprivation and brain network topology

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

UNCERTAINTY QUANTIFICATION OF PETROLEUM RESERVOIRS: A STRUCTURED BAYESIAN APPROACH

This thesis proposes a systematic Bayesian approach for uncertainty quantification with an application for petroleum reservoirs. First, we demonstrated the potential of additional misfit functions based on specific events in reservoir management, to gain knowledge about reservoir behaviour and quality in probabilistic forecasting. Water breakthrough and productivity deviation were selected and provided insights of discontinuities in simulation data when compared to the use of traditional misfit functions (e.g. production rate, BHP) alone. Second, we designed and implemented a systematic methodology for uncertainty reduction combining reservoir simulation and emulation techniques under the Bayesian History Matching for Uncertainty Reduction (BHMUR) approach. Flexibility, repeatability and scalability are the main features of this high-level structure, incorporating innovations such as phases of evaluation and multiple emulation techniques. This workflow potentially turns the practice of BHMUR more standardised across applications. It was applied for a complex case study, with 26 uncertainties, outputs from 25 wells and 11+ years of historical data based on a hypothetical reality, resulting in the construction of 115 valid emulators and a small fraction of the original search space appropriately considered non-implausible by the end of the uncertainty reduction process. Third, we expanded methodologies for critical steps in the BHMUR practice: (1) extension of statistical formulation to two-class emulators; (2) efficient selection of a combination of outputs to emulate; (3) validation of emulators based on multiple criteria; and (4) accounting for systematic and random errors in observed data. Finally, a critical step in the BHMUR approach is the quantification of model discrepancy which accounts for imperfect models aiming to represent a real physical system. We proposed a methodology to quantify the model discrepancy originated from errors in target data that are set as boundary conditions in a numerical simulator. Its application demonstrated that model discrepancy is dependent on both time and location in the input space, which is a central finding to guide the BHMUR practice in case of studies based on real fields

Quantificação de incertezas em reservatórios de petróleo : uma abordagem Bayesiana estruturada

Orientadores: Denis José Schiozer e Camila Caiado; Ian Vernon; Michael Goldstein, Guilherme Daniel AvansiTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica e Durham UniversityResumo: Essa tese propõe uma abordagem Bayesiana sistemática para quantificação de incertezas de reservatórios de petróleo. No primeiro artigo, demonstramos o potencial de funções-objetivo adicionais que são baseadas em eventos específicos da fase de gerenciamento de reservatórios, a fim de melhorar a representação do comportamento do reservatório e a qualidade da previsão probabilística. Irrupção de água e desvio de produtividade foram selecionados, proporcionando um entendimento de descontinuidades no modelo numérico e nos dados de simulação quando comparado com o uso exclusivo de funções objetivo tradicionais (por exemplo, taxa de produção). No segundo artigo, definimos e implementados uma metodologia sistemática para redução de incertezas que combina simulação de reservatórios e técnicas de emulação em uma abordagem de Ajuste de Histórico Bayesiano para Redução de Incertezas (BHMUR, Bayesian History Matching for Uncertainty Reduction, acrônimo em inglês). Flexibilidade, repetitividade e escalabilidade são as características principais dessa estrutura geral que incorpora inovações tais como fases de avaliação e múltiplas técnicas de emulação. Esse procedimento potencialmente transforma a prática de BHMUR em uma mais padronizada para diversas aplicações. Aplicamos em um estudo de caso com 26 atributos incertos, dados de produção de 25 poços e 11+ anos de dados de histórico de produção baseado em uma realidade hipotética, resultando na construção de 115 emuladores validados e uma pequena fração do espaço de busca apropriadamente considerada não-implausível ao final do processo de redução de incertezas. No terceiro artigo, expandimos metodologias para estágios críticos na prática de BHMUR: (1) extensão da formulação estatística de BHMUR para acomodar emuladores do tipo classificadores; (2) seleção efetiva de uma combinação de dados de produção para emulação; (3) validação de emuladores baseados em múltiplos critérios; e (4) consideração de erros sistemáticos e aleatórios em dados observados. No último artigo, avaliamos um passo crítico para a prática de BHMUR, que é a quantificação de discrepância do modelo para contabilizar a representação de sistemas físicos a partir de modelos imperfeitos. Propusemos uma metodologia para quantificar a discrepância do modelo originada em erros de dados medidos e informados ao simulador numérico como condição de contorno (target). A aplicação da metodologia demonstrou que a discrepância do modelo é simultaneamente dependente de tempo e da posição no espaço de busca: uma descoberta importante para orientar o processo de quantificação de incertezas em estudos de caso baseados em reservatórios de petróleo reaisAbstract: This thesis proposes a systematic Bayesian approach for uncertainty quantification with an application for petroleum reservoirs. First, we demonstrated the potential of additional misfit functions based on specific events in reservoir management, to gain knowledge about reservoir behaviour and quality in probabilistic forecasting. Water breakthrough and productivity deviation were selected and provided insights of discontinuities in simulation data when compared to the use of traditional misfit functions (e.g. production rate, BHP) alone. Second, we designed and implemented a systematic methodology for uncertainty reduction combining reservoir simulation and emulation techniques under the Bayesian History Matching for Uncertainty Reduction (BHMUR) approach. Flexibility, repeatability and scalability are the main features of this high-level structure, incorporating innovations such as phases of evaluation and multiple emulation techniques. This workflow potentially turns the practice of BHMUR more standardised across applications. It was applied for a complex case study, with 26 uncertainties, outputs from 25 wells and 11+ years of historical data based on a hypothetical reality, resulting in the construction of 115 valid emulators and a small fraction of the original searching space appropriately considered non-implausible by the end of the uncertainty reduction process. Third, we expanded methodologies for critical steps in the BHMUR practice: (1) extension of statistical formulation to two-class emulators; (2) efficient selection of a combination of outputs to emulate; (3) validation of emulators based on multiple criteria; and (4) accounting for systematic and random errors in observed data. Finally, a critical step in the BHMUR approach is the quantification of model discrepancy which accounts for imperfect models aiming to represent a real physical system. We proposed a methodology to quantify the model discrepancy originated from errors in target data that are set as boundary conditions in a numerical simulator. Its application demonstrated that model discrepancy is dependent on both time and location in the input space, which is a central finding to guide the BHMUR practice in case of studies based on real fieldsDoutoradoReservatórios e GestãoDoutora em Ciências e Engenharia de Petróleo206985/2017-7CNPQFUNCAM