A Dynamic Factor Approach to Mortality Modelling

Longevity risk has become one of the major risks facing the insurance and pensions markets globally. The trade in longevity risk is underpinned by accurate forecasting of mortality rates. Using techniques from macroeconomic forecasting, we propose a dynamic factor model of mortality that fits and forecasts mortality rates parsimoniously.We compare the forecasting quality of this model and of existing models and find that the dynamic factor model generally provides superior forecasts when applied to international mortality data. We also show that existing multifactorial models have superior fit but their forecasting performance worsens as more factors are added. The dynamic factor approach used here can potentially be further improved upon by applying an appropriate stopping rule for the number of static and dynamic factors. 

Alternative Factor Models and Heritability of the Short Leyton Obsessional Inventory-Children's Version

An alternative models framework was used to test three confirmatory factor analytic models for the Short Leyton Obsessional Inventory-Children's Version (Short LOI-CV) in a general population sample of 517 young adolescent twins (11-16 years). A one-factor model as implicit in current classification systems of Obsessive-Compulsive Disorder (OCD), a two-factor obsessions and compulsions model, and a multidimensional model corresponding to the three proposed subscales of the Short LOI-CV (labelled Obsessions/Incompleteness, Numbers/Luck and Cleanliness) were considered. The three-factor model was the only model to provide an adequate explanation of the data. Twin analyses suggested significant quantitative sex differences in heritability for both the Obsessions/Incompleteness and Numbers/Luck dimensions with these being significantly heritable in males only (heritability of 60% and 65% respectively). The correlation between the additive genetic effects for these two dimensions in males was 0.95 suggesting they largely share the same genetic risk factors.

Dynamic pricing models for used products in remanufacturing with lost-sales and uncertain quality

In this paper, we investigate the remanufacturing problem of pricing single-class used products (cores) in the face of random price-dependent returns and random demand. Specifically, we propose a dynamic pricing policy for the cores and then model the problem as a continuous-time Markov decision process. Our models are designed to address three objectives: finite horizon total cost minimization, infinite horizon discounted cost, and average cost minimization. Besides proving optimal policy uniqueness and establishing monotonicity results for the infinite horizon problem, we also characterize the structures of the optimal policies, which can greatly simplify the computational procedure. Finally, we use computational examples to assess the impacts of specific parameters on optimal price and reveal the benefits of a dynamic pricing policy. © 2013 Elsevier B.V. All rights reserved.

Automatic extraction of Reduced order models from CFD simulations for building energy modeling

Thermal comfort is defined as “that condition of mind which expresses satisfaction with the thermal environment’ [1] [2]. Field studies have been completed in order to establish the governing conditions for thermal comfort [3]. These studies showed that the internal climate of a room was the strongest factor in establishing thermal comfort. Direct manipulation of the internal climate is necessary to retain an acceptable level of thermal comfort. In order for Building Energy Management Systems (BEMS) strategies to be efficiently utilised it is necessary to have the ability to predict the effect that activating a heating/cooling source (radiators, windows and doors) will have on the room. The numerical modelling of the domain can be challenging due to necessity to capture temperature stratification and/or different heat sources (radiators, computers and human beings). Computational Fluid Dynamic (CFD) models are usually utilised for this function because they provide the level of details required. Although they provide the necessary level of accuracy these models tend to be highly computationally expensive especially when transient behaviour needs to be analysed. Consequently they cannot be integrated in BEMS. This paper presents and describes validation of a CFD-ROM method for real-time simulations of building thermal performance. The CFD-ROM method involves the automatic extraction and solution of reduced order models (ROMs) from validated CFD simulations. The test case used in this work is a room of the Environmental Research Institute (ERI) Building at the University College Cork (UCC). ROMs have shown that they are sufficiently accurate with a total error of less than 1% and successfully retain a satisfactory representation of the phenomena modelled. The number of zones in a ROM defines the size and complexity of that ROM. It has been observed that ROMs with a higher number of zones produce more accurate results. As each ROM has a time to solution of less than 20 seconds they can be integrated into the BEMS of a building which opens the potential to real time physics based building energy modelling.

The structure of the Beck Hopelessness Scale: A confirmatory factor analysis in UK students

The aim of this paper was to confirm the factor structure of the 20-item Beck Hopelessness Scale in a non-clinical population. Previous research has highlighted a lack of clarity in its construct validity with regards to this population.

Based on previous factor analytic findings from both clinical and non-clinical studies, 13 separate confirmatory factor models were specified and estimated using LISREL 8.72 to test the one, two and three-factor models.

Psychology and medical students at Queen's University, Belfast (n = 581) completed both the BHS and the Beck Depression Inventory (BDI).

All models showed reasonable fit, but only one, a four-item single-factor model demonstrated a nonsignificant chi-squared statistic. These four items can be used to derive a Short-Form BHS (SBHS) in which increasing scores (0-4) corresponded with increasing scores in the BDI. The four items were also drawn from all three of Beck's proposed triad, and included both positively and negatively scored items.

This study in a UK undergraduate non-clinical population suggests that the BHS best measures a one-factor model of hopelessness. It appears that a shorter four-item scale can also measure this one-factor model. (C) 2011 Elsevier Ltd. All rights reserved.

Response of residential electricity demand to price: The effect of measurement error

In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured.

Determining the response of African biota to climate change: using the past to model the future

Prediction of biotic responses to future climate change in tropical Africa tends to be based on two modelling approaches: bioclimatic species envelope models and dynamic vegetation models. Another complementary but underused approach is to examine biotic responses to similar climatic changes in the past as evidenced in fossil and historical records. This paper reviews these records and highlights the information that they provide in terms of understanding the local- and regional-scale responses of African vegetation to future climate change. A key point that emerges is that a move to warmer and wetter conditions in the past resulted in a large increase in biomass and a range distribution of woody plants up to 400–500 km north of its present location, the so-called greening of the Sahara. By contrast, a transition to warmer and drier conditions resulted in a reduction in woody vegetation in many regions and an increase in grass/savanna-dominated landscapes. The rapid rate of climate warming coming into the current interglacial resulted in a dramatic increase in community turnover, but there is little evidence for widespread extinctions. However, huge variation in biotic response in both space and time is apparent with, in some cases, totally different responses to the same climatic driver. This highlights the importance of local features such as soils, topography and also internal biotic factors in determining responses and resilience of the African biota to climate change, information that is difficult to obtain from modelling but is abundant in palaeoecological records.

Assessment of the double-skin façade passive thermal buffer effect.

Double Skin Façades (DSFs) are becoming increasingly popular architecture for commercial office buildings. Although DSFs are widely accepted to have the capacity to offer significant passive benefits and enable low energy building performance, there remains a paucity of knowledge with regard to their operation. Identification of the most determinant architectural parameters of DSFs is the focus of ongoing research. This paper presents an experimental and simulation study of a DSF installed on a commercial building in Dublin, Ireland. The DSF is south facing and acts to buffer the building from winter heat losses, but risks enhancing over-heating on sunny days. The façade is extensively monitored during winter months. Computational Fluid Dynamic (CFD) models are used to simulate the convective operation of the DSF. This research concludes DSFs as suited for passive, low energy architecture in temperature climates such as Ireland but identifies issues requiring attention in DSF design.

Appropriate complexity for the prediction of coastal and estuarine geomorphic behaviour at decadal to centennial scales

Coastal and estuarine landforms provide a physical template that not only accommodates diverse ecosystem functions and human activities, but also mediates flood and erosion risks that are expected to increase with climate change. In this paper, we explore some of the issues associated with the conceptualisation and modelling of coastal morphological change at time and space scales relevant to managers and policy makers. Firstly, we revisit the question of how to define the most appropriate scales at which to seek quantitative predictions of landform change within an age defined by human interference with natural sediment systems and by the prospect of significant changes in climate and ocean forcing. Secondly, we consider the theoretical bases and conceptual frameworks for determining which processes are most important at a given scale of interest and the related problem of how to translate this understanding into models that are computationally feasible, retain a sound physical basis and demonstrate useful predictive skill. In particular, we explore the limitations of a primary scale approach and the extent to which these can be resolved with reference to the concept of the coastal tract and application of systems theory. Thirdly, we consider the importance of different styles of landform change and the need to resolve not only incremental evolution of morphology but also changes in the qualitative dynamics of a system and/or its gross morphological configuration. The extreme complexity and spatially distributed nature of landform systems means that quantitative prediction of future changes must necessarily be approached through mechanistic modelling of some form or another. Geomorphology has increasingly embraced so-called ‘reduced complexity’ models as a means of moving from an essentially reductionist focus on the mechanics of sediment transport towards a more synthesist view of landform evolution. However, there is little consensus on exactly what constitutes a reduced complexity model and the term itself is both misleading and, arguably, unhelpful. Accordingly, we synthesise a set of requirements for what might be termed ‘appropriate complexity modelling’ of quantitative coastal morphological change at scales commensurate with contemporary management and policy-making requirements: 1) The system being studied must be bounded with reference to the time and space scales at which behaviours of interest emerge and/or scientific or management problems arise; 2) model complexity and comprehensiveness must be appropriate to the problem at hand; 3) modellers should seek a priori insights into what kind of behaviours are likely to be evident at the scale of interest and the extent to which the behavioural validity of a model may be constrained by its underlying assumptions and its comprehensiveness; 4) informed by qualitative insights into likely dynamic behaviour, models should then be formulated with a view to resolving critical state changes; and 5) meso-scale modelling of coastal morphological change should reflect critically on the role of modelling and its relation to the observable world.

The influence of transforming growth factor-beta1 gene polymorphisms on the severity of gingival overgrowth associated with concomitant use of cyclosporin A and a calcium channel blocker

The purpose of this study was to determine whether the prevalence and severity of gingival overgrowth in renal transplant recipients concomitantly treated with cyclosporin and a calcium channel blocker was associated with functional polymorphisms within the signal sequence of the transforming growth factor-(TGF)beta1 gene.

Simulation of Dynamic Operation of a Single-Cylinder Two-Stroke Engine

Presented is a study that expands the body of knowledge on the effect of in-cycle speed fluctuations on performance of small engines. It uses the engine and drivetrain models developed previously by Callahan, et al. (1) to examine a variety of engines. The predicted performance changes due to drivetrain effects are shown in each case, and conclusions are drawn from those results. The single-cylinder, high performance four-stroke engine showed significant changes in predicted performance compared to the prediction with zero speed fluctuation in the model. Measured speed fluctuations from a firing Yamaha YZ426 engine were applied to the simulation in addition to data from a simple free mass model. Both methods predicted similar changes in performance. The multiple-cylinder, high performance two-stroke engine also showed significant changes in performance depending on the firing configuration. With both engines, the change in performance diminished with increasing mean engine speed. The low output, single-cylinder two-stroke engine simulation showed only a negligible change in performance, even with high amplitude speed fluctuations. Because the torque versus engine speed characteristic for the engine was so flat, this was expected. The cross-charged, multi-cylinder two-stroke engine also showed only a negligible change in performance. In this case, the combination of a relatively high inertia rotating assembly and the multiple cylinder firing events within the revolution smoothing the torque pulsations reduced the speed fluctuation amplitude itself.