Refinement of the Clinical Scenario Evaluation Framework for Assessment of Competing Development Strategies with an Application to Multiple Sclerosis

When competing strategies for development programs, clinical trial designs, or data analysis methods exist, the alternatives need to be evaluated in a systematic way to facilitate informed decision making. Here we describe a refinement of the recently proposed clinical scenario evaluation framework for the assessment of competing strategies. The refinement is achieved by subdividing key elements previously proposed into new categories, distinguishing between quantities that can be estimated from preexisting data and those that cannot and between aspects under the control of the decision maker from those that are determined by external constraints. The refined framework is illustrated by an application to a design project for an adaptive seamless design for a clinical trial in progressive multiple sclerosis.

Goal-refinement appraisal of soft projects (GRASP)

Industrial projects are often complex and burdened with time pressures and a lack of information. The term 'soft-project' used here stands for projects where the ‘what’ and/or the ‘how’ is uncertain, which is often the experience in projects involving software intensive systems developments. This thesis intertwines the disciplines of project management and requirements engineering in a goal-oriented application of the maxim ‘keep all objectives satisfied’. It thus proposes a method for appraising projects. In this method, a goal-oriented analysis establishes a framework with which expert judgements are collected so as to construct a confidence profile in regard to the feasibility and adequacy of the project's planned outputs. It is hoped that this appraisal method will contribute to the activities of project ‘shaping’ and aligning stakeholders’ expectations whilst helping project managers appreciate what parts of their project can be progressed and what parts should be held pending further analysis. This thesis offers the following original contribution: an appreciation of appraisal in the project context; a goal-oriented confidence profiling technique; and: a technique to produce goal-refinement diagrams – referred to as Goal Sketching. Collectively these amount to a method for the ‘Goal Refinement Appraisal of Soft-Projects’ (GRASP). The validity of the GRASP method is shown for two projects. In the first it is used for shaping a business investigation project. This is done in real-time in the project. The second case is a retrospective study of an enterprise IT project. This case tests the effectiveness of forecasting project difficulty from an initial confidence profile.

Anisotropic refinement of the structure of Thermoascus aurantiacusxylanase I

The isotropic crystallographic model of the structure of xylanase I from Thermoascus aurantiacus (TAXI) has now been refined anisotropically at 1.14 Å resolution to a standard residual of R = 11.1% for all data. TAXI is amongst the five largest proteins deposited in the Protein Data Bank to have been refined with anisotropic displacement parameters (ADPs) at this level of resolution. The anisotropy analysis revealed a more isotropic distribution of anisotropy than usually observed previously. Adding ADPs resulted in high-quality electron-density maps which revealed discrepancies from the previously suggested primary sequences for this enzyme. Side-chain conformational disorder was modelled for 16 residues, including Trp275, a bulky residue at the active site. An unrestrained refinement was consistent with the protonation of the catalytic acid/base glutamate and the deprotonation of the nucleophile glutamate, as required for catalysis. The thermal stability of TAXI is reinterpreted in the light of the new refined model.

Early warning with calibrated and sharper probabilistic forecasts

Given a nonlinear model, a probabilistic forecast may be obtained by Monte Carlo simulations. At a given forecast horizon, Monte Carlo simulations yield sets of discrete forecasts, which can be converted to density forecasts. The resulting density forecasts will inevitably be downgraded by model mis-specification. In order to enhance the quality of the density forecasts, one can mix them with the unconditional density. This paper examines the value of combining conditional density forecasts with the unconditional density. The findings have positive implications for issuing early warnings in different disciplines including economics and meteorology, but UK inflation forecasts are considered as an example.

A detailed single chain model for molten poly(tetrafluoroethylene) from a novel structure refinement technique on neutron scattering data

We present a new methodology that couples neutron diffraction experiments over a wide Q range with single chain modelling in order to explore, in a quantitative manner, the intrachain organization of non-crystalline polymers. The technique is based on the assignment of parameters describing the chemical, geometric and conformational characteristics of the polymeric chain, and on the variation of these parameters to minimize the difference between the predicted and experimental diffraction patterns. The method is successfully applied to the study of molten poly(tetrafluoroethylene) at two different temperatures, and provides unambiguous information on the configuration of the chain and its degree of flexibility. From analysis of the experimental data a model is derived with CC and CF bond lengths of 1.58 and 1.36 Å, respectively, a backbone valence angle of 110° and a torsional angle distribution which is characterized by four isometric states, namely a split trans state at ± 18°, giving rise to a helical chain conformation, and two gauche states at ± 112°. The probability of trans conformers is 0.86 at T = 350°C, which decreases slightly to 0.84 at T = 400°C. Correspondingly, the chain segments are characterized by long all-trans sequences with random changes in sign, rather anisotropic in nature, which give rise to a rather stiff chain. We compare the results of this quantitative analysis of the experimental scattering data with the theoretical predictions of both force fields and molecular orbital conformation energy calculations.

Reliability, sufficiency, and the decomposition of proper scores

Scoring rules are an important tool for evaluating the performance of probabilistic forecasting schemes. A scoring rule is called strictly proper if its expectation is optimal if and only if the forecast probability represents the true distribution of the target. In the binary case, strictly proper scoring rules allow for a decomposition into terms related to the resolution and the reliability of a forecast. This fact is particularly well known for the Brier Score. In this article, this result is extended to forecasts for finite-valued targets. Both resolution and reliability are shown to have a positive effect on the score. It is demonstrated that resolution and reliability are directly related to forecast attributes that are desirable on grounds independent of the notion of scores. This finding can be considered an epistemological justification of measuring forecast quality by proper scoring rules. A link is provided to the original work of DeGroot and Fienberg, extending their concepts of sufficiency and refinement. The relation to the conjectured sharpness principle of Gneiting, et al., is elucidated.

Regularized logistic models for probabilistic forecasting and diagnostics

Logistic models are studied as a tool to convert dynamical forecast information (deterministic and ensemble) into probability forecasts. A logistic model is obtained by setting the logarithmic odds ratio equal to a linear combination of the inputs. As with any statistical model, logistic models will suffer from overfitting if the number of inputs is comparable to the number of forecast instances. Computational approaches to avoid overfitting by regularization are discussed, and efficient techniques for model assessment and selection are presented. A logit version of the lasso (originally a linear regression technique), is discussed. In lasso models, less important inputs are identified and the corresponding coefficient is set to zero, providing an efficient and automatic model reduction procedure. For the same reason, lasso models are particularly appealing for diagnostic purposes.

Probabilistic evaluation of time series models : a comparison of several approaches

Several methods are examined which allow to produce forecasts for time series in the form of probability assignments. The necessary concepts are presented, addressing questions such as how to assess the performance of a probabilistic forecast. A particular class of models, cluster weighted models (CWMs), is given particular attention. CWMs, originally proposed for deterministic forecasts, can be employed for probabilistic forecasting with little modification. Two examples are presented. The first involves estimating the state of (numerically simulated) dynamical systems from noise corrupted measurements, a problem also known as filtering. There is an optimal solution to this problem, called the optimal filter, to which the considered time series models are compared. (The optimal filter requires the dynamical equations to be known.) In the second example, we aim at forecasting the chaotic oscillations of an experimental bronze spring system. Both examples demonstrate that the considered time series models, and especially the CWMs, provide useful probabilistic information about the underlying dynamical relations. In particular, they provide more than just an approximation to the conditional mean.

Probabilistic forecasting: why model imperfection is a poison pill

This volume is a serious attempt to open up the subject of European philosophy of science to real thought, and provide the structural basis for the interdisciplinary development of its specialist fields, but also to provoke reflection on the idea of ‘European philosophy of science’. This efforts should foster a contemporaneous reflection on what might be meant by philosophy of science in Europe and European philosophy of science, and how in fact awareness of it could assist philosophers interpret and motivate their research through a stronger collective identity. The overarching aim is to set the background for a collaborative project organising, systematising, and ultimately forging an identity for, European philosophy of science by creating research structures and developing research networks across Europe to promote its development.

A probabilistic analysis of the future potential of evaporative cooling systems in a temperate climate

The probabilistic projections of climate change for the United Kingdom (UK Climate Impacts Programme) show a trend towards hotter and drier summers. This suggests an expected increase in cooling demand for buildings – a conflicting requirement to reducing building energy needs and related CO2 emissions. Though passive design is used to reduce thermal loads of a building, a supplementary cooling system is often necessary. For such mixed-mode strategies, indirect evaporative cooling is investigated as a low energy option in the context of a warmer and drier UK climate. Analysis of the climate projections shows an increase in wet-bulb depression; providing a good indication of the cooling potential of an evaporative cooler. Modelling a mixed-mode building at two different locations, showed such a building was capable of maintaining adequate thermal comfort in future probable climates. Comparing the control climate to the scenario climate, an increase in the median of evaporative cooling load is evident. The shift is greater for London than for Glasgow with a respective 71.6% and 3.3% increase in the median annual cooling load. The study shows evaporative cooling should continue to function as an effective low-energy cooling technique in future, warming climates.