Rolling resistance contribution to a road pavement life cycle carbon footprint analysis.

PURPOSE: Although the impact of road pavement surface condition on rolling resistance has been included in the life cycle assessment (LCA) framework of several studies in the last years, there is still a high level of uncertainty concerning the methodological assumptions and the parameters that can affect the results. In order to adopt pavement carbon footprint/LCA as a decision-making tool, it is necessary to explore the impact of the chosen methods and assumptions on the LCA results. METHODS: This paper provides a review of the main models describing the impact of the pavement surface properties on vehicle fuel consumption and analyses the influence of the methodological assumptions related to the rolling resistance on the LCA results. It compares the CO2 emissions, calculated with two different rolling resistance models existing in literature, and performs a sensitivity test on some specific input variables (pavement deterioration rate, traffic growth, and emission factors/fuel efficiency improvement). RESULTS AND DISCUSSION: The model used to calculate the impact of the pavement surface condition on fuel consumption significantly affects the LCA results. The pavement deterioration rate influences the calculation in both models, while traffic growth and fuel efficiency improvement have a limited impact on the vehicle CO2 emissions resulting from the pavement condition contribution to rolling resistance. CONCLUSIONS AND RECOMMENDATIONS: Existing models linking pavement condition to rolling resistance and hence vehicle emissions are not broadly applicable to the use phase of road pavement LCA and further research is necessary before a widely-used methodology can be defined. The methods of modelling and the methodological assumptions need to be transparent in the analysis of the impact of the pavement surface condition on fuel consumption, in order to be interpreted by decision makers and implemented in an LCA framework. This will be necessary before product category rules (PCR) for pavement LCA can be extended to include the use phase.

Metabolism by conjugation appears to confer resistance to paracetamol (acetaminophen) hepatotoxicity in the cynomolgus monkey.

1. Paracetamol overdose remains the leading cause of acute liver failure in humans. This study was undertaken in cynomolgus monkeys to study the pharmacokinetics, metabolism and the potential for hepatotoxic insult from paracetamol administration as a possible model for human toxicity. 2. No adverse effects were observed for doses of up to 900 mg/kg/d for 14 d. Only minor sporadic increases in alanine aminotransferase, aspartate aminotransferase and glutamate dehydrogenase in a number of animals were observed, with no clear dose response. 3. Toxicokinetic analysis showed good plasma exposure, albeit with less than proportional rises in Cmax and AUC, with increasing dose. The Cmax values in monkey were up to 3.5 times those associated with human liver toxicity and the AUC approx. 1000 times those associated with liver enzyme changes in 31-44% of human subjects. 4. Metabolite profiling of urine by (1)H NMR spectroscopy revealed paracetamol and its glucuronide and sulphate metabolites. Glutathione-derived metabolites, e.g. the cysteinyl conjugate, were only present in very low concentrations whilst the mercapturate was not detected. 5. These in vivo observations demonstrated that the cynomolgus monkey is remarkably resistant to paracetamol-induced toxicity and a poor model for investigating paracetamol-related hepatotoxicity in humans.

Evaluation of the pharmacodynamics and pharmacokinetics of the PARP inhibitor olaparib: a phase I multicentre trial in patients scheduled for elective breast cancer surgery.

Olaparib (AZD2281) is an oral poly(ADP-ribose) polymerase (PARP) inhibitor with antitumour activity in cancer patients with BRCA1/2 germline mutations and in patients with homologous recombination deficiency. In this dose-finding study, patients were randomized to olaparib 10, 30, 100, 200 or 400 mg (capsule formulation) twice daily for the 4-5 days preceding breast cancer surgery. The primary objective was to identify an effective biological dose of olaparib for future trials. Secondary endpoints included evaluation of PARP-1 inhibition dose/exposure-response, and safety. Olaparib plasma pharmacokinetics (PK) and the pharmacodynamics (PD) in tumour and peripheral blood mononuclear cells (PBMCs) were evaluated. Population PK/PD modelling was performed on pooled data from this study and a previously reported study. Sixty patients were randomized (n = 12, each dose). Dose-dependent increases in exposure to olaparib were observed, but at ~50 % lower plasma exposure levels than seen in advanced disease studies. The mean maximal extent of PARP inhibition in PBMCs and tumour tissue was 50.6 % and 70.0 %, respectively, and was similar to inhibitory levels reported previously. No PARP inhibition-dose relationship was observed. Due to the unexpectedly low olaparib exposure, we were unable to determine an effective biological dose. Common adverse events included procedural pain (n = 31 patients), nausea, asthenia, malaise and increased blood creatinine (n = 6, each); these were of mild-to-moderate intensity, and all were manageable. Despite low olaparib exposure, PARP inhibition was consistent with previous reports. Reasons for the inter-study differences in exposure are unclear. The tolerability profile of olaparib was consistent with previous studies.

Performance of Plant-Produced Asphalt Containing Cellular Capsules.

This paper aims to assess the influence of encapsulated rejuvenators on plant-produced asphalt's performance. The polymeric capsules are evaluated as cellular materials that deform and absorb energy while they experience a progressive collapse of their porous structure, rather than a simply means to release the rejuvenator. Additionally, variables during asphalt manufacturing that may affect their plastic deformation under loading are assessed too. Firstly, plant-produced asphalt's mechanical and morphological properties were evaluated, including the capsules' distribution and integrity after mixing. Then, results were contrasted with lab-produced asphalt under controlled conditions. Lastly, the capsules' deformation was qualitatively evaluated using a FE model to verify findings from the testing campaign. It was concluded that (i) cellular capsules can resist mixing at an asphalt plant without compromising their performance; (ii) the deformation of the capsules affected asphalt's stability by up to 13%, reduced the particle loss by up to 25% and increased asphalt's macrotexture by 10%; (iii) to maximize their energy absorption, the cellular capsules must be part of the aggregate skeleton.

Integrating human factors and operational research in a multidisciplinary investigation of road maintenance.

There has been limited collaboration between researchers in human factors and operational research disciplines, particularly in relation to work in complex, distributed systems. This study aimed to investigate work at the interface between human factors and operational research in the case example of road resurfacing work. Descriptive material on the factors affecting performance in road maintenance work was collected with support from a range of human factors-based methods and was used to inform operational research analyses. Investigation of the case example from a different perspective, for the supply of asphalt from a distribution centre to multiple work locations, gave a broader picture of the complexity and challenges for the improvement of road maintenance processes. Factors affecting performance in the road maintenance context have been assessed for their potential for further investigation using an integrated human factors and operational research approach. Relative strengths of the disciplines and a rationale for ongoing, collaborative work are described. STATEMENT OF RELEVANCE: The paper provides evidence of the potential benefits of greater collaboration across human factors and operational research disciplines, using investigation of a case example in the complex, distributed system of road resurfacing.

Analysing truck harsh braking incidents to study roundabout accident risk.

In order to reduce accident risk, highway authorities prioritise maintenance budgets partly based upon previous accident history. However, as accident rates have continued to fall, this approach has become problematic as accident 'black spots' have been treated and the number of accidents at any individual site has fallen, making previous accident history a less reliable indicator of future accident risk. Another way of identifying sites of higher accident risk might be to identify near-miss accidents (where an accident nearly happened but was avoided). The principal aim of this paper is to analyze potentially unsafe truck driving conditions from counts of Harsh Braking Incidents (HBIs) at roundabouts and compare the results to similar, previous studies of accident numbers at the same sites, to explore if HBIs can be studied as a surrogate for accidents. This is achieved by processing truck telematics data with geo-referenced incidents of harsh braking. Models are then developed to characterise the relationships between truck HBIs and geometric and traffic variables. These HBIs are likely to occur more often than accidents and may, therefore, be useful in identifying sites with high accident risk. Based on the results of this study, it can be concluded that HBIs are influenced by traffic and geometric variables in a similar way to accidents; therefore they may be useful in considering accident risk at roundabouts. They are a source of higher volumes of data than accidents, which is important in considering changes or trends in accident risk over time. The results showed that random-parameters count data models provide better goodness of fit compared to fixed-parameters models and more variables were found to be significant, giving a better prediction of events.

Discovery, synthesis, and in vivo activity of a new class of pyrazoloquinazolines as selective inhibitors of aurora B kinase.

The Aurora kinases have been the subject of considerable interest as targets for the development of new anticancer agents. While evidence suggests inhibition of Aurora B kinase gives rise to the more pronounced antiproliferative phenotype, the most clinically advanced agents reported to date typically inhibit both Aurora A and B. We have discovered a series of pyrazoloquinazolines, some of which show greater than 1000-fold selectivity for Aurora B over Aurora A kinase activity, in recombinant enzyme assays. These compounds have been designed for parenteral administration and achieve high levels of solubility by virtue of their ability to be delivered as readily activated phosphate derivatives. The prodrugs are comprehensively converted to the des-phosphate form in vivo, and the active species have advantageous pharmacokinetic properties and safety pharmacology profiles. The compounds display striking in vivo activity, and compound 5 (AZD1152) has been selected for clinical evaluation and is currently in phase 1 clinical trials.

Multiscale Shannon's Entropy Modeling of Orientation and Distance in Steel Fiber Micro-Tomography Data.

This paper is concerned with the modeling and analysis of the orientation and distance between steel fibers in X-ray micro-tomography data. The advantage of combining both orientation and separation in a model is that it helps provide a detailed understanding of how the steel fibers are arranged, which is easy to compare. The developed models are designed to summarize the randomness of the orientation distribution of the steel fibers both locally and across an entire volume based on multiscale entropy. Theoretical modeling, simulation, and application to real imaging data are shown here. The theoretical modeling of multiscale entropy for orientation includes a proof showing the final form of the multiscale taken over a linear range of scales. A series of image processing operations are also included to overcome interslice connectivity issues to help derive the statistical descriptions of the orientation distributions of the steel fibers. The results demonstrate that multiscale entropy provides unique insights into both simulated and real imaging data of steel fiber reinforced concrete.

A comparison of the quantitative methods for the analysis of the platinum-containing anticancer drug [cis-[amminedichloro(2-methylpyridine)]platinum(II)] (ZD0473) by HPLC coupled to either a triple quadrupole mass spectrometer or an inductively coupled plasma mass spectrometer.

The use of high performance liquid chromatography coupled with inductively coupled plasma mass spectrometry (HPLC-ICPMS) as means for the quantitative determination of ZD0473, a platinum anticancer drug, and its related biologically active "aqua" compounds in biofluid samples is described. The performance of the resulting HPLC-ICPMS method was compared with that of a conventional HPLC-triple quadrupole mass spectrometer-based (HPLC-MS/MS) system for properties such as limit of detection, linearity, and reproducibility using spiked samples. The methods were then applied to the determination of plasma ultrafitrate concentrations of ZD0473 in dog plasma samples obtained following intravenous and oral administration at 0.5 and 6 mg/kg, respectively. These experiments showed that both methods were capable of providing accurate and precise results but that the HPLC-ICPMS method had advantages of extended linear range and superior sensitivity, providing a limit of quantification of 0.1 ng/mL for ZD0473, as compared to 5 ng/mL using the current HPLC-MS/MS method. In addition, by using a single combined HPLC-ICPMS/MS/MS system, it was possible to determine the relative MS/MS response of the aqua compounds for the first time.