Exploring spatial non‐stationarity in the social determinants of time to work

Social differences in time to work are a growing concern of transport planning, as they can increase the risk of social exclusion of some groups. Recent work has found that those differences tend to vary across the urban space. Geographic Weighted Regression models this variability by estimating relationships in each place, weighting data by distance to that place. This paper builds on this work by assuming that households and policy-makers make decisions over space by comparing places according to their function within the metropolitan space, regardless of their geographic proximity. The determinants of time to work then vary in the space defined by variables identifying that function. This procedure is applied to the case of the Lisbon Metropolitan Area at two moments in time. Higher times to work are associated with less-qualified populations, with the strength of the relationships generally increasing with centrality in relation to employment locations and dependence on jobs in the main metropolitan centre. The priority to investments in road transport in the period concerned extended the disadvantages to second-ring suburban areas

Multiple transport disadvantages: A cluster analysis of the socio-spatial distribution of levels of accessibility and pedestrian mobility in a metropolitan area.

The concept of social justice is increasingly called upon in the assessment of the social and environmental sustainability of urban transport. This paper brings together two strands of the literature on this topic: the role of accessibility in social inclusion and the distribution of the environmental impacts of transport. Using the Lisbon Metropolitan Area as case study, we test if there are cumulative social inequalities in terms of accessibility and pedestrian mobility, considering that the latter depends on local environmental quality. We use GIS methods to estimate a series of neighbourhood-level indicators, such as private and public transport accessibility to jobs and urban facilities, community severance and pedestrian exposure to traffic noise. Neighbourhoods are then classified based on the scores of those indicators at two moments in time. We found six clusters. Accessibility increases and pedestrian mobility decreases as we move from the ‘main centre’ towards the ‘suburban’, ‘small centres’, ‘semi-rural’ and ‘rural’ clusters. A sixth cluster is labelled ‘multiple disadvantages’ and groups dispersed neighbourhoods that fare poorly in all indicators. The clusters are then characterized in terms of their socio-economic composition. We find that central areas usually have elderly populations, while rural areas and the “multiple disadvantaged” cluster tend to have low-qualified populations. We also test if disadvantages based on a neighbourhood’s location persist after accounting for the daily destinations and travel modes used by its population. We find that ‘multiple disadvantaged’ areas have the poorest scores in time to work, effects of congestion, and pedestrian noise exposures for commuters on the way to work. The main conclusion is that ‘hotspots’ of multiple transport-related disadvantages tend to have populations traditionally at risk of social exclusion. More emphasis should be put on locally-based interventions on and public participation methods in the definition of strategies for urban transport planning

Development of high-throughput methods to screen disease caused by Rhizoctonia solani AG 2-1 in oilseed rape

Background: Rhizoctonia solani (Kühn) is a soil-borne, necrotrophic fungus causing damping off, root rot and stem canker in many cultivated plants worldwide. Oilseed rape (OSR, Brassica napus) is the primary host for anastomosis group (AG) 2-1 of R. solani causing pre- and post-emergence damping-off resulting in death of seedlings and impaired crop establishment. Presently, there are no known resistant OSR genotypes and the main methods for disease control are fungicide seed treatments and cultural practices. The identification of sources of resistance for crop breeding is essential for sustainable management of the disease. However, a high-throughput, reliable screening method for resistance traits is required. The aim of this work was to develop a low cost, rapid screening method for disease phenotyping and identification of resistance traits. Results: Four growth systems were developed and tested: (1) nutrient media plates, (2) compost trays, (3) light expanded clay aggregate (LECA) trays, and (4) a hydroponic pouch and wick system. Seedlings were inoculated with virulent AG 2-1 to cause damping-off disease and grown for a period of 4–10 days. Visual disease assessments were carried out or disease was estimated through image analysis using ImageJ. Conclusion: Inoculation of LECA was the most suitable method for phenotyping disease caused by R. solani AG 2-1 as it enabled the detection of differences in disease severity among OSR genotypes within a short time period whilst allowing measurements to be conducted on whole plants. This system is expected to facilitate identification of resistant germplasm

The performance of stochastic designs in wellbore drilling operations

© 2018, The Author(s). Wellbore drilling operations frequently entail the combination of a wide range of variables. This is underpinned by the numerous factors that must be considered in order to ensure safety and productivity. The heterogeneity and sometimes unpredictable behaviour of underground systems increases the sensitivity of drilling activities. Quite often the operating parameters are set to certify effective and efficient working processes. However, failings in the management of drilling and operating conditions sometimes result in catastrophes such as well collapse or fluid loss. This study investigates the hypothesis that optimising drilling parameters, for instance mud pressure, is crucial if the margin of safe operating conditions is to be properly defined. This was conducted via two main stages: first a deterministic analysis—where the operating conditions are predicted by conventional modelling procedures—and then a probabilistic analysis via stochastic simulations—where a window of optimised operation conditions can be obtained. The outcome of additional stochastic analyses can be used to improve results derived from deterministic models. The incorporation of stochastic techniques in the evaluation of wellbore instability indicates that margins of the safe mud weight window are adjustable and can be extended considerably beyond the limits of deterministic predictions. The safe mud window is influenced and hence can also be amended based on the degree of uncertainty and the permissible level of confidence. The refinement of results from deterministic analyses by additional stochastic simulations is vital if a more accurate and reliable representation of safe in situ and operating conditions is to be obtained during wellbore operations.Published versio

Enteric-coated sodium bicarbonate supplementation improves high-intensity cycling performance in trained cyclists

Purpose: Enteric-coated sodium bicarbonate (NaHCO3) can attenuate gastrointestinal (GI) symptoms following acute bicarbonate loading, although the subsequent effects on exercise performance have not been investigated. The purpose of this study was to examine the effects of enteric-coated NaHCO3 supplementation on high-intensity exercise performance and GI symptoms. Methods: Eleven trained male cyclists completed three 4 km time trials after consuming; a placebo or 0.3 g∙kg–1 body mass NaHCO3 in enteric-coated or gelatin capsules. Exercise trials were timed with individual peak blood bicarbonate ion concentration ([HCO3–]). Blood acid–base balance was measured pre-ingestion, pre-exercise, and post-exercise, whereas GI symptoms were recorded pre-ingestion and immediately pre-exercise. Results: Pre-exercise blood [HCO3−] and potential hydrogen (pH) were greater for both NaHCO3 conditions (P &lt; 0.0005) when compared to placebo. Performance time was faster with enteric-coated (− 8.5 ± 9.6 s, P = 0.044) and gelatin (− 9.6 ± 7.2 s, P = 0.004) NaHCO3 compared to placebo, with no significant difference between conditions (mean difference = 1.1 ± 5.3 s, P = 1.000). Physiological responses were similar between conditions, although blood lactate ion concentration was higher with gelatin NaHCO3 (2.4 ± 1.7 mmol∙L–1, P = 0.003) compared with placebo. Furthermore, fewer participants experienced GI symptoms with enteric-coated (n = 3) compared to gelatin (n = 7) NaHCO3. Discussion: Acute enteric-coated NaHCO3 consumption mitigates GI symptoms at the onset of exercise and improves subsequent 4 km cycling TT performance. Athletes who experience GI side-effects after acute bicarbonate loading may, therefore, benefit from enteric-coated NaHCO3 supplementation prior to exercise performance.</p

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Search for direct pair production of the top squark in all-hadronic final states in proton-proton collisions at s√=8 TeV with the ATLAS detector

The results of a search for direct pair production of the scalar partner to the top quark using an integrated luminosity of 20.1fb−1 of proton–proton collision data at √s = 8 TeV recorded with the ATLAS detector at the LHC are reported. The top squark is assumed to decay via t˜→tχ˜01 or t˜→ bχ˜±1 →bW(∗)χ˜01 , where χ˜01 (χ˜±1 ) denotes the lightest neutralino (chargino) in supersymmetric models. The search targets a fully-hadronic final state in events with four or more jets and large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits are reported in terms of the top squark and neutralino masses and as a function of the branching fraction of t˜ → tχ˜01 . For a branching fraction of 100%, top squark masses in the range 270–645 GeV are excluded for χ˜01 masses below 30 GeV. For a branching fraction of 50% to either t˜ → tχ˜01 or t˜ → bχ˜±1 , and assuming the χ˜±1 mass to be twice the χ˜01 mass, top squark masses in the range 250–550 GeV are excluded for χ˜01 masses below 60 GeV

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Design of Experiments for Screening

The aim of this paper is to review methods of designing screening experiments, ranging from designs originally developed for physical experiments to those especially tailored to experiments on numerical models. The strengths and weaknesses of the various designs for screening variables in numerical models are discussed. First, classes of factorial designs for experiments to estimate main effects and interactions through a linear statistical model are described, specifically regular and nonregular fractional factorial designs, supersaturated designs and systematic fractional replicate designs. Generic issues of aliasing, bias and cancellation of factorial effects are discussed. Second, group screening experiments are considered including factorial group screening and sequential bifurcation. Third, random sampling plans are discussed including Latin hypercube sampling and sampling plans to estimate elementary effects. Fourth, a variety of modelling methods commonly employed with screening designs are briefly described. Finally, a novel study demonstrates six screening methods on two frequently-used exemplars, and their performances are compared

Informational entropy : a failure tolerance and reliability surrogate for water distribution networks

Evolutionary algorithms are used widely in optimization studies on water distribution networks. The optimization algorithms use simulation models that analyse the networks under various operating conditions. The solution process typically involves cost minimization along with reliability constraints that ensure reasonably satisfactory performance under abnormal operating conditions also. Flow entropy has been employed previously as a surrogate reliability measure. While a body of work exists for a single operating condition under steady state conditions, the effectiveness of flow entropy for systems with multiple operating conditions has received very little attention. This paper describes a multi-objective genetic algorithm that maximizes the flow entropy under multiple operating conditions for any given network. The new methodology proposed is consistent with the maximum entropy formalism that requires active consideration of all the relevant information. Furthermore, an alternative but equivalent flow entropy model that emphasizes the relative uniformity of the nodal demands is described. The flow entropy of water distribution networks under multiple operating conditions is discussed with reference to the joint entropy of multiple probability spaces, which provides the theoretical foundation for the optimization methodology proposed. Besides the rationale, results are included that show that the most robust or failure-tolerant solutions are achieved by maximizing the sum of the entropies