A proposed validation framework for expert elicited Bayesian Networks

The popularity of Bayesian Network modelling of complex domains using expert elicitation has raised questions of how one might validate such a model given that no objective dataset exists for the model. Past attempts at delineating a set of tests for establishing confidence in an entirely expert-elicited model have focused on single types of validity stemming from individual sources of uncertainty within the model. This paper seeks to extend the frameworks proposed by earlier researchers by drawing upon other disciplines where measuring latent variables is also an issue. We demonstrate that even in cases where no data exist at all there is a broad range of validity tests that can be used to establish confidence in the validity of a Bayesian Belief Network.

A two-metal ion mechanism operates in the hammerhead ribozyme-mediated cleavage of an RNA substrate

Evidence for a two-metal ion mechanism for cleavage of the HH16 hammerhead ribozyme is provided by monitoring the rate of cleavage of the RNA substrate as a function of La3+ concentration in the presence of a constant concentration of Mg2+. We show that a bell-shaped curve of cleavage activation is obtained as La3+ is added in micromolar concentrations in the presence of 8 mM Mg2+, with a maximal rate of cleavage being attained in the presence of 3 microM La3+. These results show that two-metal ion binding sites on the ribozyme regulate the rate of the cleavage reaction and, on the basis of earlier estimates of the Kd values for Mg2+ of 3.5 mM and > 50 mM, that these sites bind La3+ with estimated Kd values of 0.9 and > 37.5 microM, respectively. Furthermore, given the very different effects of these metal ions at the two binding sites, with displacement of Mg2+ by La3+ at the stronger (relative to Mg2+) binding site activating catalysis and displacement of Mg2+ by La3+ at the weaker (relative to Mg2+) (relative to Mg2+) binding site inhibiting catalysis, we show that the metal ions at these two sites play very different roles. We argue that the metal ion at binding site 1 coordinates the attacking 2'-oxygen species in the reaction and lowers the pKa of the attached proton, thereby increasing the concentration of the attacking alkoxide nucleophile in an equilibrium process. In contrast, the role of the metal ion at binding site 2 is to catalyze the reaction by absorbing the negative charge that accumulates at the leaving 5'-oxygen in the transition state. We suggest structural reasons why the Mg(2+)-La3+ ion combination is particularly suited to demonstrating these different roles of the two-metal ions in the ribozyme cleavage reaction.

Modeling train delays in urban networks

The reliability of urban passenger trains is a critical performance measure for passenger satisfaction and ultimately market share. A delay to one train in a peak period can have a severe effect on the schedule adherence of other trains. This paper presents an analytically based model to quantify the expected positive delay for individual passenger trains and track links in an urban rail network. The model specifically addresses direct delay to trains, knock-on delays to other trains, and delays at scheduled connections. A solution to the resultant system of equations is found using an iterative refinement algorithm. Model validation, which is carried out using a real-life suburban train network consisting of 157 trains, shows the model estimates to be on average within 8% of those obtained from a large scale simulation. Also discussed, is the application of the model to assess the consequences of increased scheduled slack time as well as investment strategies designed to reduce delay.

Active ageing among older adults with lifelong intellectual disabilities : the role of familial and nonfamilial social networks

Little research has examined the extent to which active ageing is facilitated by family and nonfamilial support persons of older adults with intellectual disabilities. This study explores the role played by key unpaid carers/support persons of older adults with lifelong intellectual disabilities in facilitating "active ageing." Little research has examined the extent to which active ageing is facilitated by family and nonfamilial support persons of older adults with intellectual disabilities. This study explores the role played by key unpaid carers/support persons of older adults with lifelong intellectual disabilities in facilitating “active ageing.” All key social network members conceived active ageing to mean ongoing activity. Family and extended family members were found to play a crucial role in facilitating independent living and providing opportunities for recreational pursuits for those living in group homes. Members of religious organizations and group home staff provided the same types of opportunities where family support was absent. The findings suggest the need for improvements in resource provision, staff training, and group home policy and building design.

Excess power circulation in distribution networks containing distributed energy resources

The presence of large number of single-phase distributed energy resources (DERs) can cause severe power quality problems in distribution networks. The DERs can be installed in random locations. This may cause the generation in a particular phase exceeds the load demand in that phase. Therefore the excess power in that phase will be fed back to the transmission network. To avoid this problem, the paper proposes the use of distribution static compensator (DSTATCOM) that needs to be connected at the first bus following a substation. When operated properly, the DSTATCOM can facilitate a set of balanced current flow from the substation, even when excess power is generated by DERs. The proposals are validated through extensive digital computer simulation studies using PSCAD and MATLAB.

Fusing loop detector and probe vehicle data to estimate travel time statistics on signalized urban networks

This article presents a methodology that integrates cumulative plots with probe vehicle data for estimation of travel time statistics (average, quartile) on urban networks. The integration reduces relative deviation among the cumulative plots so that the classical analytical procedure of defining the area between the plots as the total travel time can be applied. For quartile estimation, a slicing technique is proposed. The methodology is validated with real data from Lucerne, Switzerland and it is concluded that the travel time estimates from the proposed methodology are statistically equivalent to the observed values.

Inquiries, empirical research and regulatory failure

The paper reveals that regulatory failure, often chronic, has characterised the regulatory environments of charities across time and locale. The analysis of the primary literature identifies common issues and suggested remedies pertaining to the regulatory failures of charities. These issues may well be appropriate for consideration by the commission and participants given their persistence in various inquiries for nearly four centuries. Such inquiries also considered other issues not directly referred to in this paper, to also include them would exponentially increase the already unwieldy size of this paper.

An approach for current balancing in distribution networks with rooftop PVs

Current unbalance is a significant power quality problem in distribution networks. This problem increases further with the increased penetration of single-phase photovoltaic cells. In this paper, a new approach is developed for current unbalance reduction in medium voltage distribution networks. The method is based on utilization of three single-phase voltage source converters connected in delta configuration between the phases. Each converter is controlled to function as a varying capacitor. The combination of the load and the compensator will result in a balanced load with unity power factor. The efficacy of the proposed current unbalance reduction concept is verified through dynamic simulations in PSCAD/EMTDC.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.