Optimal Scheduling of Trains on a Single Line Track

This paper describes the development and use of a model designed to optimise train schedules on single line rail corridors. The model has been developed with two major applications in mind, namely: as a decision support tool for train dispatchers to schedule trains in real time in an optimal way; and as a planning tool to evaluate the impact of timetable changes, as well as railroad infrastructure changes. The mathematical programming model described here schedules trains over a single line track. The priority of each train in a conflict depends on an estimate of the remaining crossing and overtaking delay, as well as the current delay. This priority is used in a branch and bound procedure to allow and optimal solution to reasonable size train scheduling problems to be determined efficiently. The use of the model in an application to a 'real life' problem is discussed. The impacts of changing demand by increasing the number of trains, and reducing the number of sidings for a 150 kilometre section of single line track are discussed. It is concluded that the model is able to produce useful results in terms of optimal schedules in a reasonable time for the test applications shown here

Nurse perceptions of family home-visiting programs in Australia and England

Aims: Nurse home-visiting programs are employed to enhance the functioning of disadvantaged mothers and young children. Despite the key role played by nurses, there is little empirical evidence describing the views and experiences of nurses who deliver home-visiting programs. This study compared the views and experiences of nurses delivering home-visiting programs in England and South Australia. Methods: Participants were 108 nurses delivering the South Australian Family Home Visiting program (2008 – 2011), and 44 nurses delivering the Family Nurse Partnership program in England (2007 – 2009). Data were collected using a standard questionnaire that was completed by nurses in each country. The questionnaire asked nurses about their level of influence on program outcomes, approaches they used to retain maternal engagement with the home-visiting programs, barriers to effective program delivery and the effectiveness of supervision. Results: Both groups of nurses considered that their greatest influence was improving mothers’ confidence with parenting skills and increasing mothers’ knowledge about children's development. Each group identified quality of nurse-mother relationships as the factor most relevant to retaining maternal engagement. Other influential factors were flexibility of timing for visits and the capacity of the programs to meet specific needs of mothers

Factors Associated with Marburg Hemorrhagic Fever:

Background. Reliable on-site polymerase chain reaction (PCR) testing for Marburg hemorrhagic fever (MHF) is not always available. Therefore, clinicians triage patients on the basis of presenting symptoms and contact history. Using patient data collected in Uige, Angola, in 2005, we assessed the sensitivity and specificity of these factors to evaluate the validity of World Health Organization (WHO)–recommended case definitions for MHF. Methods. Multivariable logistic regression was used to identify independent predictors of PCR confirmation of MHF. A data-derived algorithm was developed to obtain new MHF case definitions with improved sensitivity and specificity. Results. A MHF case definition comprising (1) an epidemiological link or (2) the combination of myalgia or arthralgia and any hemorrhage could potentially serve as an alternative to current case definitions. Our dataderived case definitions maintained the sensitivity and improved the specificity of current WHO-recommended case definitions. Conclusions. Continued efforts to improve clinical documentation during filovirus outbreaks would aid in the refinement of case definitions and facilitate outbreak control

Potential neural substrates underlying circadian and olfactory disruptions in preclinical Alzheimer’s disease

Alzheimer’s disease (AD) is the leading cause of dementia, with over 45 million patients worldwide, and poses significant economic and emotional burdens to both patients and caregivers, significantly raising the number of those affected. Unfortunately, much of the existing research on the disease only addresses a small subset of associated symptomologies and pathologies. In this review, we propose to target the earliest stages of the disease, when symptomology first arises. In these stages, before the onset of hallmark symptoms of AD such as cognitive impairments and memory loss, circadian and olfactory disruptions arise and are detectable. Functional similarities between circadian and olfactory systems provide a basis upon which to seek out common mechanisms in AD which may target them early on in the disease. Existing studies of interactions between these systems, while intriguing, leave open the question of the neural substrates underlying them. Potential substrates for such interactions are proposed in this review, such as indirect projections that may functionally connect the two systems and dopaminergic signaling. These substrates may have significant implications for mechanisms underlying disruptions to circadian and olfactory function in early stages of AD. In this review, we propose early detection of AD using a combination of circadian and olfactory deficits and subsequent early treatment of these deficits may provide profound benefits to both patients and caregivers. Additionally, we suggest that targeting research toward the intersection of these two systems in AD could uncover mechanisms underlying the broader set of symptoms and pathologies that currently elude researchers

Computational study of structural and elastic properties of random AlGaInN alloys

In this work we present a detailed computational study of structural and elastic properties of cubic AlGaInN alloys in the framework of Keating valence force field model, for which we perform accurate parametrization based on state of the art DFT calculations. When analyzing structural properties, we focus on concentration dependence of lattice constant, as well as on the distribution of the nearest and the next nearest neighbour distances. Where possible, we compare our results with experiment and calculations performed within other computational schemes. We also present a detailed study of elastic constants for AlGaInN alloy over the whole concentration range. Moreover, we include there accurate quadratic parametrization for the dependence of the alloy elastic constants on the composition. Finally, we examine the sensitivity of obtained results to computational procedures commonly employed in the Keating model for studies of alloys

INFX GUIDE: DEPARTMENT OF ENERGY BILATERAL AGREEMENTS FOR COOPERATION IN THE FIELD OF RADIOACTIVE WASTE MANAGEMENT (INFX: INTERNATIONAL INFORMATION EXCHANGE)

As the U. S. Department of Energy (DOE) and DOE contractors have increased the magnitude and scope of their cooperative activities with other nations in the nuclear fuel cycle and waste management field, a need has developed for ready sources of information concerning foreign waste management programs, DOE technology exchange policies, bilateral fuel cycle and waste management agreements and plans and activities to implement those agreements. The INFX (International InLormation E~change) Guide is one of a series of documents that have been prepared to provide that information. The INFX Guide has been compiled under the charter of PNL's International Support Office (IPSO) to maintain for DOE a center to collect, organize, evaluate and disseminate information on foreign and international radioactive waste management programs. Because the information in this document is constantly subject to change, the document is assembled in loose-leaf form to accommodate frequent updates

Preliminary analysis of New Zealand scampi (Metanephrops challengeri) diet using metabarcoding

Deep sea lobsters are highly valued for seafood and provide the basis of important commercial fisheries in many parts of the world. Despite their economic significance, relatively little is known about their natural diets. Microscopic analyses of foregut content in some species have suffered from low taxonomic resolution, with many of the dietary items difficult to reliably identify as their tissue is easily digested. DNA metabarcoding has the potential to provide greater taxonomic resolution of the diet of the New Zealand scampi (Metanephrops challengeri) through the identification of gut contents, but a number of methodological concerns need to be overcome first to ensure optimum DNA metabarcoding results. In this study, a range of methodological parameters were tested to determine the optimum protocols for DNA metabarcoding, and provide a first view of M. challengeri diet. Several PCR protocols were tested, using two universal primer pairs targeting the 18S rRNA and COI genes, on DNA extracted from both frozen and ethanol preserved samples for both foregut and hindgut digesta. The selection of appropriate DNA polymerases, buffers and methods for reducing PCR inhibitors (including the use of BSA) were found to be critical. Amplification from frozen or ethanol preserved gut contents appeared similarly dependable. The COI gene was found to be more effective than 18S rRNA gene for identifying large eukaryotic taxa from the digesta; however, it was less successfully amplified. The 18S rRNA gene was more easily amplified, but identified mostly smaller marine organisms such as plankton and parasites. This preliminary analysis of the diet of M. challengeri identified a range of species (13,541 reads identified as diet), which included the ghost shark (Hydrolagus novaezealandiae), silver warehou (Seriolella punctata), tall sea pen (Funiculina quadrangularis) and the salp (Ihlea racovitzai), suggesting that they have a varied diet, with a high reliance on scavenging a diverse range of pelagic and benthic species from the seafloor

Predictive response-relevant clustering of expression data provides insights into disease processes

This article describes and illustrates a novel method of microarray data analysis that couples model-based clustering and binary classification to form clusters of ;response-relevant' genes; that is, genes that are informative when discriminating between the different values of the response. Predictions are subsequently made using an appropriate statistical summary of each gene cluster, which we call the ;meta-covariate' representation of the cluster, in a probit regression model. We first illustrate this method by analysing a leukaemia expression dataset, before focusing closely on the meta-covariate analysis of a renal gene expression dataset in a rat model of salt-sensitive hypertension. We explore the biological insights provided by our analysis of these data. In particular, we identify a highly influential cluster of 13 genes-including three transcription factors (Arntl, Bhlhe41 and Npas2)-that is implicated as being protective against hypertension in response to increased dietary sodium. Functional and canonical pathway analysis of this cluster using Ingenuity Pathway Analysis implicated transcriptional activation and circadian rhythm signalling, respectively. Although we illustrate our method using only expression data, the method is applicable to any high-dimensional datasets