Second best toll and capacity optimisation in network: solution algorithm and policy implications

This paper looks at the first and second-best jointly optimal toll and road capacity investment problems from both policy and technical oriented perspectives. On the technical side, the paper investigates the applicability of the constraint cutting algorithm for solving the second-best problem under elastic demand which is formulated as a bilevel programming problem. The approach is shown to perform well despite several problems encountered by our previous work in Shepherd and Sumalee (2004). The paper then applies the algorithm to a small sized network to investigate the policy implications of the first and second-best cases. This policy analysis demonstrates that the joint first best structure is to invest in the most direct routes while reducing capacities elsewhere. Whilst unrealistic this acts as a useful benchmark. The results also show that certain second best policies can achieve a high proportion of the first best benefits while in general generating a revenue surplus. We also show that unless costs of capacity are known to be low then second best tolls will be affected and so should be analysed in conjunction with investments in the network

Subglacial lake drainage detected beneath the Greenland ice sheet

The contribution of the Greenland ice sheet to sea-level rise has accelerated in recent decades. Subglacial lake drainage events can induce an ice sheet dynamic response—a process that has been observed in Antarctica, but not yet in Greenland, where the presence of subglacial lakes has only recently been discovered. Here we investigate the water flow paths from a subglacial lake, which drained beneath the Greenland ice sheet in 2011. Our observations suggest that the lake was fed by surface meltwater flowing down a nearby moulin, and that the draining water reached the ice margin via a subglacial tunnel. Interferometric synthetic aperture radar-derived measurements of ice surface motion acquired in 1995 suggest that a similar event may have occurred 16 years earlier, and we propose that, as the climate warms, increasing volumes of surface meltwater routed to the bed will cause such events to become more common in the future

Adjusting for BMI in analyses of volumetric mammographic density and breast cancer risk

Abstract Background Fully automated assessment of mammographic density (MD), a biomarker of breast cancer risk, is being increasingly performed in screening settings. However, data on body mass index (BMI), a confounder of the MD–risk association, are not routinely collected at screening. We investigated whether the amount of fat in the breast, as captured by the amount of mammographic non-dense tissue seen on the mammographic image, can be used as a proxy for BMI when data on the latter are unavailable. Methods Data from a UK case control study (numbers of cases/controls: 414/685) and a Norwegian cohort study (numbers of cases/non-cases: 657/61059), both with volumetric MD measurements (dense volume (DV), non-dense volume (NDV) and percent density (%MD)) from screening-age women, were analysed. BMI (self-reported) and NDV were taken as measures of adiposity. Correlations between BMI and NDV, %MD and DV were examined after log-transformation and adjustment for age, menopausal status and parity. Logistic regression models were fitted to the UK study, and Cox regression models to the Norwegian study, to assess associations between MD and breast cancer risk, expressed as odds/hazard ratios per adjusted standard deviation (OPERA). Adjustments were first made for standard risk factors except BMI (minimally adjusted models) and then also for BMI or NDV. OPERA pooled relative risks (RRs) were estimated by fixed-effect models, and between-study heterogeneity was assessed by the I 2 statistics. Results BMI was positively correlated with NDV (adjusted r = 0.74 in the UK study and r = 0.72 in the Norwegian study) and with DV (r = 0.33 and r = 0.25, respectively). Both %MD and DV were positively associated with breast cancer risk in minimally adjusted models (pooled OPERA RR (95% confidence interval): 1.34 (1.25, 1.43) and 1.46 (1.36, 1.56), respectively; I 2 = 0%, P >0.48 for both). Further adjustment for BMI or NDV strengthened the %MD–risk association (1.51 (1.41, 1.61); I 2 = 0%, P = 0.33 and 1.51 (1.41, 1.61); I 2 = 0%, P = 0.32, respectively). Adjusting for BMI or NDV marginally affected the magnitude of the DV–risk association (1.44 (1.34, 1.54); I 2 = 0%, P = 0.87 and 1.49 (1.40, 1.60); I 2 = 0%, P = 0.36, respectively). Conclusions When volumetric MD–breast cancer risk associations are investigated, NDV can be used as a measure of adiposity when BMI data are unavailable

Solar ultraviolet-B radiation and vitamin D: a cross-sectional population-based study using data from the 2007 to 2009 Canadian Health Measures Survey

Background: Exposure to solar ultraviolet-B (UV-B) radiation is a major source of vitamin D3. Chemistry climate models project decreases in ground-level solar erythemal UV over the current century. It is unclear what impact this will have on vitamin D status at the population level. The purpose of this study was to measure the association between ground-level solar UV-B and serum concentrations of 25-hydroxyvitamin D (25(OH)D) using a secondary analysis of the 2007 to 2009 Canadian Health Measures Survey (CHMS). Methods: Blood samples collected from individuals aged 12 to 79 years sampled across Canada were analyzed for 25(OH)D (n=4,398). Solar UV-B irradiance was calculated for the 15 CHMS collection sites using the Tropospheric Ultraviolet and Visible Radiation Model. Multivariable linear regression was used to evaluate the association between 25(OH)D and solar UV-B adjusted for other predictors and to explore effect modification. Results: Cumulative solar UV-B irradiance averaged over 91 days (91-day UV-B) prior to blood draw correlated significantly with 25(OH)D. Independent of other predictors, a 1 kJ/m 2 increase in 91-day UV-B was associated with a significant 0.5 nmol/L (95% CI 0.3-0.8) increase in mean 25(OH)D (P =0.0001). The relationship was stronger among younger individuals and those spending more time outdoors. Based on current projections of decreases in ground-level solar UV-B, we predict less than a 1 nmol/L decrease in mean 25(OH)D for the population. Conclusions: In Canada, cumulative exposure to ambient solar UV-B has a small but significant association with 25(OH)D concentrations. Public health messages to improve vitamin D status should target safe sun exposure with sunscreen use, and also enhanced dietary and supplemental intake and maintenance of a healthy body weight

Cost-effectiveness of initiating extrafine- or standard size-particle inhaled corticosteroid for asthma in two health-care systems: a retrospective matched cohort study

Data acquisition and analyses were funded by Teva Pharmaceuticals

Whole exome sequencing coupled with unbiased functional analysis reveals new Hirschsprung disease genes

published_or_final_versio

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

A role for β-catenin in diet-induced skeletal muscle insulin resistance.

A central characteristic of insulin resistance is the impaired ability for insulin to stimulate glucose uptake into skeletal muscle. While insulin resistance can occur distal to the canonical insulin receptor-PI3k-Akt signaling pathway, the signaling intermediates involved in the dysfunction are yet to be fully elucidated. β-catenin is an emerging distal regulator of skeletal muscle and adipocyte insulin-stimulated GLUT4 trafficking. Here, we investigate its role in skeletal muscle insulin resistance. Short-term (5-week) high-fat diet (HFD) decreased skeletal muscle β-catenin protein expression 27% (p = 0.03), and perturbed insulin-stimulated β-cateninS552 phosphorylation 21% (p = 0.009) without affecting insulin-stimulated Akt phosphorylation relative to chow-fed controls. Under chow conditions, mice with muscle-specific β-catenin deletion had impaired insulin responsiveness, whereas under HFD, both mice exhibited similar levels of insulin resistance (interaction effect of genotype × diet p < 0.05). Treatment of L6-GLUT4-myc myocytes with palmitate lower β-catenin protein expression by 75% (p = 0.02), and attenuated insulin-stimulated β-catenin phosphorylationS552 and actin remodeling (interaction effect of insulin × palmitate p < 0.05). Finally, β-cateninS552 phosphorylation was 45% lower in muscle biopsies from men with type 2 diabetes while total β-catenin expression was unchanged. These findings suggest that β-catenin dysfunction is associated with the development of insulin resistance.fals

Detection and attribution of human influence on regional precipitation

Understanding how human influence on climate is affecting precipitation around the world is immensely important for defining mitigation policies, and for adaptation planning. Yet despite increasing evidence for the influence of climate change on global patterns of precipitation, and expectations that significant changes in regional precipitation should have already occurred as a result of human influence on climate, compelling evidence of anthropogenic fingerprints on regional precipitation is obscured by observational and modelling uncertainties and is likely to remain so using current methods for years to come. This is in spite of substantial ongoing improvements in models, new reanalyses and a satellite record that spans over thirty years. If we are to quantify how human-induced climate change is affecting the regional water cycle, we need to consider novel ways of identifying the effects of natural and anthropogenic influences on precipitation that take full advantage of our physical expectations

Psychological responses to the proximity of climate change

A frequent suggestion to increase individuals’ willingness to take action on climate change and to support relevant policies is to highlight its proximal consequences. However, previous studies that have tested this proximising approach have not revealed the expected positive effects on individual action and support for addressing climate change. We present three lines of psychological reasoning that provide compelling arguments as to why highlighting proximal impacts of climate change might not be as effective a way to increase individual mitigation and adaptation efforts as is often assumed. Our contextualisation of the proximising approach within established psychological research suggests that, depending on the particular theoretical perspective one takes to this issue, and on specific individual characteristics suggested by these perspectives, proximising can bring about the intended positive effects, can have no (visible) effect, or can even backfire. Thus, the effects of proximising are much more complex than is commonly assumed. Revealing this complexity contributes to a refined theoretical understanding of the role psychological distance plays in the context of climate change and opens up further avenues for future research and for interventions