Supplementary information : weighted tree kernels for sequence analysis

Genomic sequences are fundamentally text documents, admitting various representations according to need and tokenization. Gene expression depends crucially on binding of enzymes to the DNA sequence at small, poorly conserved binding sites, limiting the utility of standard pattern search. However, one may exploit the regular syntactic structure of the enzyme's component proteins and the corresponding binding sites, framing the problem as one of detecting grammatically correct genomic phrases. In this paper we propose new kernels based on weighted tree structures, traversing the paths within them to capture the features which underpin the task. Experimentally, we and that these kernels provide performance comparable with state of the art approaches for this problem, while offering significant computational advantages over earlier methods. The methods proposed may be applied to a broad range of sequence or tree-structured data in molecular biology and other domains.

Analysis of construction dispute review boards

The construction industry has long been burdened with inherent adversarial relationships among the parties and the resulting disputes. Dispute review boards (DRBs) have emerged as alternatives to settle construction-related disputes outside courts. Although DRBs have found support in some quarters of the construction industry, the quantitative assessment of the impact of DRBs has not been adequately addressed. This paper presents the results of a research project undertaken to assess the impact of DRBs on the construction program of a large-scale highway agency. Three dimensions of DRB impact were assessed: (1) influence on project cost and schedule performance, (2) effectiveness of DRBs in preventing and resolving construction disputes, and (3) costs of DRB implementation. The analyses encompass data from approximately 3,000 projects extending over a 10-year period (2000–2009). Quantitative measures of performance were developed and analyzed for each category. Projects that used DRBs faced reduced costs and schedule growth (6.88 and 12.92%, respectively) when compared to non-DRB projects (11.53 and 28.96%). DRBs were also found to be effective in avoiding and settling disputes; the number of arbitration cases reduced consistently after DRB implementation, and DRBs have a success rate of 97% in settling disputes for which DRBs were used. Moreover, costs of DRBs were found to comprise a relatively small fraction (i.e., approximately 0.3%) of total project budgets. It was concluded that DRBs were effective dispute prevention and resolution alternatives with no significant adverse effects on project performance.

Critical analysis of spam prevention techniques

E-mail spam has remained a scourge and menacing nuisance for users, internet and network service operators and providers, in spite of the anti-spam techniques available; and spammers are relentlessly circumventing these anti-spam techniques embedded or installed in form of software products on both client and server sides of both fixed and mobile devices to their advantage. This continuous evasion degrades the capabilities of these anti-spam techniques as none of them provides a comprehensive reliable solution to the problem posed by spam and spammers. Major problem for instance arises when these anti-spam techniques misjudge or misclassify legitimate emails as spam (false positive); or fail to deliver or block spam on the SMTP server (false negative); and the spam passes-on to the receiver, and yet this server from where it originates does not notice or even have an auto alert service to indicate that the spam it was designed to prevent has slipped and moved on to the receiver’s SMTP server; and the receiver’s SMTP server still fail to stop the spam from reaching user’s device and with no auto alert mechanism to inform itself of this inability; thus causing a staggering cost in loss of time, effort and finance. This paper takes a comparative literature overview of some of these anti-spam techniques, especially the filtering technological endorsements designed to prevent spam, their merits and demerits to entrench their capability enhancements, as well as evaluative analytical recommendations that will be subject to further research.

Managing cost implications for highway infrastructure sustainability

Highway construction works have significant bearings on all aspects of sustainability. With the increasing level of public awareness and government regulatory measures, the construction industry is experiencing a cultural shift to recognise, embrace and pursue sustainability. Stakeholders are now keen to identify sustainable alternatives and the financial implications of including them on a lifecycle basis. They need tools that can aid the evaluation of investment options. To date, however, there have not been many financial assessments on the sustainability aspects of highway projects. This is because the existing life-cycle costing analysis (LCCA) models tend to focus on economic issues alone and are not able to deal with sustainability factors. This paper provides insights into the current practice of life-cycle cost analysis, and the identification and quantification of sustainability-related cost components in highway projects through literature review, questionnaire surveys and semi-structured interviews. The results can serve as a platform for highway project stakeholders to develop practical tools to evaluate highway investment decisions and reach an optimum balance between financial viability and sustainability deliverables.

Recursive pathways to marginal likelihood estimation with prior-sensitivity analysis

We investigate the utility to computational Bayesian analyses of a particular family of recursive marginal likelihood estimators characterized by the (equivalent) algorithms known as "biased sampling" or "reverse logistic regression" in the statistics literature and "the density of states" in physics. Through a pair of numerical examples (including mixture modeling of the well-known galaxy dataset) we highlight the remarkable diversity of sampling schemes amenable to such recursive normalization, as well as the notable efficiency of the resulting pseudo-mixture distributions for gauging prior-sensitivity in the Bayesian model selection context. Our key theoretical contributions are to introduce a novel heuristic ("thermodynamic integration via importance sampling") for qualifying the role of the bridging sequence in this procedure, and to reveal various connections between these recursive estimators and the nested sampling technique.

Lumbar epidural steroids are not cost effective in sciatica

Background Lumbar Epidural Steroids Injections (ESI’s) have previously been shown to provide some degree of pain relief in sciatica. Number Needed To Treat (NNT) to achieve 50% pain relief has been estimated at 7 from the results of randomised controlled trials. Pain relief is temporary. They remain one of the most commonly provided procedures in the UK. It is unknown whether this pain relief represents good value for money. Methods 228 patients were randomised into a multi-centre Double Blind Randomised Controlled Trial. Subjects received up to 3 ESI’s or intra-spinous saline depending on response and fall off with the first injection. All other treatments were permitted. All received a review of analgesia, education and physical therapy. Quality of life was assessed using the SF36 at 6 points and compared using independent sample t-tests. Follow up was up to 1 yr. Missing data was imputed using last observation carried forward (LOCF). QALY’s (Quality of Life Years) were derived from preference based heath values (summary health utility score). SF-6D health state classification was derived from SF-36 raw score data. Standard gambles (SG) were calculated using Model 10. SG scores were calculated on trial results. LOCF was not used for this. Instead average SG were derived for a subset of patients with observations for all visits up to week 12. Incremental QALY’s were derived as the difference in the area between the SG curve for the active group and placebo group. Results SF36 domains showed a significant improvement in pain at week 3 but this was not sustained (mean 54 Active vs 61 Placebo P<0.05). Other domains did not show any significant gains compared with placebo. For derivation of SG the number in the sample in each period differed. In week 12, average SG scores for active and placebo converged. In other words, the health gain for the active group as measured by SG was achieved by the placebo group by week 12. The incremental QALY gained for a patient under the trial protocol compared with the standard care package was 0.0059350. This is equivalent to an additional 2.2 days of full health. The cost per QALY gained to the provider from a patient management strategy administering one epidural as suggested by results was £25 745.68. This result was derived assuming that the gain in QALY data calculated for patients under the trial protocol would approximate that under a patient management strategy based on the trial results (one ESI). This is above the threshold suggested by some as a cost effective treatment. Conclusions The transient benefit in pain relief afforded by ESI’s does not appear to be cost-effective. Further work is needed to develop more cost-effective conservative treatments for sciatica.

Examining the effects of early cost drivers on contingencies

The accuracy of early cost estimates is critical to the success of construction projects. The selected tender price (clients' building cost) is usually seen in previous research as a holistic dependent variable when examining early stage estimates. Unlike other components of construction cost, the amount of contingencies is decided by clients/consultants with consideration of early project information. Cost drivers of contingencies estimates are associated with uncertainty and complexity, and include project size, schedule, ground condition, construction site access, market condition and so on. A path analysis of 133 UK school building contracts was conducted to identify impacts of nine major cost drivers on the determination of contingencies by different clients/cost estimators. This research finds that gross floor area (GFA), schedule and requirement of air conditioning have statistically significant impacts on the contingency determination. The mediating role of schedule between gross floor area and contingencies (GFA→Schedule→Contingencies) was confirmed with the Soble test. The total effects of the three variables on contingencies estimates were obtained with the consideration of this indirect effect. The squared multiple correlation (SMC) of contingencies (=0.624) indicates the identified three variables can explain 62.4% variance of contingencies, and it is comparatively satisfactory considering the heterogeneity among different estimators, unknown estimating techniques and different projects

The impact of a congestion charging exemption on the demand for new low‐emission vehicles

Numerous initiatives have been employed around the world in order to address rising greenhouse gas (GHG) emissions originating from the transport sector. These measures include: travel demand management (congestion‐charging), increased fuel taxes, alternative fuel subsidies and low‐emission vehicle (LEV) rebates. Incentivizing the purchase of LEVs has been one of the more prevalent approaches in attempting to tackle this global issue. LEVs, whilst having the advantage of lower emissions and, in some cases, more efficient fuel consumption, also bring the downsides of increased purchase cost, reduced convenience of vehicle fuelling, and operational uncertainty. To stimulate demand in the face of these challenges, various incentive‐based policies, such as toll exemptions, have been used by national and local governments to encourage the purchase of these types of vehicles. In order to address rising GHG emissions in Stockholm, and in line with the Swedish Government’s ambition to operate a fossil free fleet by 2030, a number of policies were implemented targeting the transport sector. Foremost amongst these was the combination of a congestion charge – initiated to discourage emissions‐intensive travel – and an exemption from this charge for some LEVs, established to encourage a transition towards a ‘green’ vehicle fleet. Although both policies shared the aim of reducing GHG emissions, the exemption for LEVs carried the risk of diminishing the effectiveness of the congestion charging scheme. As the number of vehicle owners choosing to transition to an eligible LEV increased, the congestion‐reduction effectiveness of the charging scheme weakened. In fact, policy makers quickly recognized this potential issue and consequently phased out the LEV exemption less than 18 months after its introduction (1). Several studies have investigated the demand for LEVs through stated‐preference (SP) surveys across multiple countries, including: Denmark (2), Germany (3, 4), UK (5), Canada (6), USA (7, 8) and Australia (9). Although each of these studies differed in approach, all involved SP surveys where differing characteristics between various types of vehicles, including LEVs, were presented to respondents and these respondents in turn made hypothetical decisions about which vehicle they would be most likely to purchase. Although these studies revealed a number of interesting findings in regards to the potential demand for LEVs, they relied on SP data. In contrast, this paper employs an approach where LEV choice is modelled by taking a retrospective view and by using revealed preference (RP) data. By examining the revealed preferences of vehicle owners in Stockholm, this study overcomes one of the principal limitations of SP data, namely that stated preferences may not in fact reflect individuals’ actual choices, such as when cost, time, and inconvenience factors are real rather than hypothetical. This paper’s RP approach involves modelling the characteristics of individuals who purchased new LEVs, whilst estimating the effect of the congestion charging exemption upon choice probabilities and subsequent aggregate demand. The paper contributes to the current literature by examining the effectiveness of a toll exemption under revealed preference conditions, and by assessing the total effect of the policy based on key indicators for policy makers, including: vehicle owner home location, commuting patterns, number of children, age, gender and income. Extended Abstract Submission for Kuhmo Nectar Conference 2014 2 The two main research questions motivating this study were:  Which individuals chose to purchase a new LEV in Stockholm in 2008?; and,  How did the congestion charging exemption affect the aggregate demand for new LEVs in Stockholm in 2008? In order to answer these research questions the analysis was split into two stages. Firstly, a multinomial logit (MNL) model was used to identify which demographic characteristics were most significantly related to the purchase of an LEV over a conventional vehicle. The three most significant variables were found to be: intra‐cordon residency (positive); commuting across the cordon (positive); and distance of residence from the cordon (negative). In order to estimate the effect of the exemption policy on vehicle purchase choice, the model included variables to control for geographic differences in preferences, based on the location of the vehicle owners’ homes and workplaces in relation to the congestion‐charging cordon boundary. These variables included one indicator representing commutes across the cordon and another indicator representing intra‐cordon residency. The effect of the exemption policy on the probability of purchasing LEVs was estimated in the second stage of the analysis by focusing on the groups of vehicle owners that were most likely to have been affected by the policy i.e. those commuting across the cordon boundary (in both directions). Given the inclusion of the indicator variable representing commutes across the cordon, it is assumed that the estimated coefficient of this variable captures the effect of the exemption policy on the utility of choosing to purchase an exempt LEV for these two groups of vehicle owners. The intra‐cordon residency indicator variable also controls for differences between the two groups, based upon direction of travel across the cordon boundary. A counter‐hypothesis to this assumption is that the coefficient of the variable representing commuting across the cordon boundary instead only captures geo‐demographic differences that lead to variations in LEV ownership across the different groups of vehicle owners in relation to the cordon boundary. In order to address this counter‐hypothesis, an additional analysis was performed on data from a city with a similar geodemographic pattern to Stockholm, Gothenburg ‐ Sweden’s second largest city. The results of this analysis provided evidence to support the argument that the coefficient of the variable representing commutes across the cordon was capturing the effect of the exemption policy. Based upon this framework, the predicted vehicle type shares were calculated using the estimated coefficients of the MNL model and compared with predicted vehicle type shares from a simulated scenario where the exemption policy was inactive. This simulated scenario was constructed by setting the coefficient for the variable representing commutes across the cordon boundary to zero for all observations to remove the utility benefit of the exemption policy. Overall, the procedure of this second stage of the analysis led to results showing that the exemption had a substantial effect upon the probability of purchasing and aggregate demand for exempt LEVs in Stockholm during 2008. By making use of unique evidence of revealed preferences of LEV owners, this study identifies the common characteristics of new LEV owners and estimates the effect of Stockholm's congestion charging exemption upon the demand for new LEVs during 2008. It was found that the variables that had the greatest effect upon the choice of purchasing an exempt LEV included intra‐cordon residency (positive), distance of home from the cordon (negative), and commuting across the cordon (positive). It was also determined that owners under the age of 30 years preferred non‐exempt LEVs (low CO2 LEVs), whilst those over the age of 30 years preferred electric vehicles. In terms of electric vehicles, it was apparent that those individuals living within the city had the highest propensity towards purchasing this vehicle type. A negative relationship between choosing an electric vehicle and the distance of an individuals’ residency from the cordon was also evident. Overall, the congestion charging exemption was found to have increased the share of exempt LEVs in Stockholm by 1.9%, with, as expected, a much stronger effect on those commuting across the boundary, with those living inside the cordon having a 13.1% increase, and those owners living outside the cordon having a 5.0% increase. This increase in demand corresponded to an additional 538 (+/‐ 93; 95% C.I.) new exempt LEVs purchased in Stockholm during 2008 (out of a total of 5 427; 9.9%). Policy makers can take note that an incentive‐based policy can increase the demand for LEVs and appears to be an appropriate approach to adopt when attempting to reduce transport emissions through encouraging a transition towards a ‘green’ vehicle fleet.

An analysis of dispute review boards and settlement mediation as used in the Australian construction industry

If there is a silver lining to the adversarial, dispute-prone nature of the building and construction industry, it can be found in the concomitant rise of innovative dispute resolution mechanisms. Time, cost and relationship concerns have meant that the formal adversarial system holds little appeal for disputing parties. As these alternative forms of dispute avoidance/resolution have matured in Australia over the last 20 years, attention has turned to the key characteristics of each process and their suitability to the building and construction industry. This article considers the role of dispute review boards (DRBs) and mediation as two alternative methods for avoiding/resolving disputes in the construction industry. Criteria are established for evaluating the efficacy of these procedures and their sensitivity to the needs of construction industry disputants. The ultimate conclusion reached is that DRBs represent a powerful, yet underutilised dispute resolution tool in Australia, and possess many industry-specific advantages that more traditional forms of alternative dispute resolution (particularly mediation) do not provide.

Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for vibration-based Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data asynchronicity and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. Based on a brief review, this paper first reveals that Data Synchronization Error (DSE) is the most inherent factor amongst uncertainties of SHM-oriented WSNs. Effects of this factor are then investigated on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when merging data from multiple sensor setups. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as benchmark data after being added with a certain level of noise to account for the higher presence of this factor in SHM-oriented WSNs. From this source, a large number of simulations have been made to generate multiple DSE-corrupted datasets to facilitate statistical analyses. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with DSE at a relaxed level. Finally, the combination of preferred OMA techniques and the use of the channel projection for the time-domain OMA technique to cope with DSE are recommended.

Confirmatory factor analysis of the baby eating behaviour questionnaire and associations with infant weight, gender and feeding mode in an Australian sample

The aim of this study was to evaluate the factor structure of the Baby Eating Behaviour Questionnaire (BEBQ) in an Australian community sample of mother-infant dyads. A secondary aim was to explore the relationship between the BEBQ subscales and infant gender, weight and current feeding mode. Confirmatory factor analysis (CFA) utilising structural equation modelling examined the hypothesised 4-factor model of the BEBQ. Only mothers (N=467) who completed all items on the BEBQ (infant age: M=17 weeks, SD=3 weeks) were included in the analysis. The original 4-factor model did not provide an acceptable fit to the data due to poor performance of the Satiety responsiveness factor. Removal of this factor (3 items) resulted in a well-fitting 3-factor model. Cronbach’s α was acceptable for the Enjoyment of food (α=0.73), Food responsiveness (α=0.78) and Slowness in eating (α=0.68) subscales but low for the Satiety responsiveness (α=0.56) subscale. Enjoyment of food was associated with higher infant weight whereas Slowness in eating and Satiety responsiveness were both associated with lower infant weight. Differences on all four subscales as a function of feeding mode were observed. This study is the first to use CFA to evaluate the hypothesised factor structure of the BEBQ. Findings support further development work on the Satiety responsiveness subscale in particular, but confirm the utility of the Enjoyment of food, Food responsiveness and Slowness in eating subscales.

Condition monitoring and fault diagnosis of diesel engines using instantaneous angular speed analysis

Continuous monitoring of diesel engine performance is critical for early detection of fault developments in an engine before they materialize into a functional failure. Instantaneous crank angular speed (IAS) analysis is one of a few nonintrusive condition monitoring techniques that can be utilized for such a task. Furthermore, the technique is more suitable for mass industry deployments than other non-intrusive methods such as vibration and acoustic emission techniques due to the low instrumentation cost, smaller data size and robust signal clarity since IAS is not affected by the engine operation noise and noise from the surrounding environment. A combination of IAS and order analysis was employed in this experimental study and the major order component of the IAS spectrum was used for engine loading estimation and fault diagnosis of a four-stroke four-cylinder diesel engine. It was shown that IAS analysis can provide useful information about engine speed variation caused by changing piston momentum and crankshaft acceleration during the engine combustion process. It was also found that the major order component of the IAS spectra directly associated with the engine firing frequency (at twice the mean shaft rotating speed) can be utilized to estimate engine loading condition regardless of whether the engine is operating at healthy condition or with faults. The amplitude of this order component follows a distinctive exponential curve as the loading condition changes. A mathematical relationship was then established in the paper to estimate the engine power output based on the amplitude of this order component of the IAS spectrum. It was further illustrated that IAS technique can be employed for the detection of a simulated exhaust valve fault in this study.

The impact of nurse practitioner services on cost, quality of care, satisfaction and wait times in the emergency department: A systematic review

Aims To provide the best available evidence to determine the impact of nurse practitioner services on cost, quality of care, satisfaction and waiting times in the emergency department for adult patients. Background The delivery of quality care in the emergency department is one of the most important service indicators in health delivery. Increasing service pressures in the emergency department have resulted in the adoption of service innovation models: the most common and rapidly expanding of these is emergency nurse practitioner services. The rapid uptake of emergency nurse practitioner service in Australia has outpaced the capacity to evaluate this service model in terms of outcomes related to safety and quality of patient care. Previous research is now outdated and not commensurate with the changing domain of delivering emergency care with nurse practitioner services. Data A comprehensive search of four electronic databases from 2006-­‐2013 was conducted to identify research evaluating nurse practitioner service impact in the emergency department. English language articles were sought using MEDLINE, CINAHL, Embase and Cochrane and included two previous systematic reviews completed five and seven years ago. Methods A three step approach was used. Following a comprehensive search, two reviewers assessed identified studies against the inclusion criteria. From the original 1013 studies, 14 papers were retained for critical appraisal on methodological quality by two independent reviewers and data extracted using standardised tools. Results Narrative synthesis was conducted to summarise and report the findings as insufficient data was available for meta-­‐analysis of results. This systematic review has shown that emergency nurse practitioner service has a positive impact on quality of care, patient satisfaction and waiting times. There was insufficient evidence to draw conclusions regarding impact on costs. Conclusion Synthesis of the available research attempts to provide an evidence base for emergency nurse practitioner service to guide healthcare leaders, policy makers and clinicians in reforming emergency department service provision. The findings suggest that further quality research is required for comparative measures of clinical and service effectiveness of emergency nurse practitioner service. In the context of increased health service demand and the need to provide timely and effective care to patients, such measures will assist in delivering quality patient care.

Perturbing event logs to identify cost reduction opportunities: a genetic algorithm-based approach

Organisations are constantly seeking new ways to improve operational efficiencies. This research study investigates a novel way to identify potential efficiency gains in business operations by observing how they are carried out in the past and then exploring better ways of executing them by taking into account trade-offs between time, cost and resource utilisation. This paper demonstrates how they can be incorporated in the assessment of alternative process execution scenarios by making use of a cost environment. A genetic algorithm-based approach is proposed to explore and assess alternative process execution scenarios, where the objective function is represented by a comprehensive cost structure that captures different process dimensions. Experiments conducted with different variants of the genetic algorithm evaluate the approach's feasibility. The findings demonstrate that a genetic algorithm-based approach is able to make use of cost reduction as a way to identify improved execution scenarios in terms of reduced case durations and increased resource utilisation. The ultimate aim is to utilise cost-related insights gained from such improved scenarios to put forward recommendations for reducing process-related cost within organisations.