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

Collaborative research exploring mental health service user perspectives on acute inpatient occupational therapy

Introduction:User perspectives are important for understanding why people engage with occupational therapy during an admission for acute mental health issues, and can be used to inform service provision and development. Method: Twenty-two recent and current inpatients participated in six semi-structured individual interviews and three focus groups. Data from the two methods were initially subject to separate thematic analysis. Then a further stage of constant comparative analysis, of both data sets, generated the findings presented here. Findings: Three themes were identified: (1) ‘A tiny sort of world’ expressed experiences of being restricted; (2) ‘Relief’ indicated how occupational therapy offered relief from the ward and experiences of mental ill-health; and (3) ‘Something to do’ suggested specific purposes for engaging in occupation. These themes indicate how service users experience and value occupational therapy for different reasons at different times. The approach of occupational therapists to service users, valuing them as occupational beings, is a key aspect of their experience. Conclusion: The profession is challenged to design flexible opportunities for occupational engagement which simultaneously provide relief and distraction, address diverse occupational needs, and are feasible within the resource restrictions of acute mental health services

Social interactions through the eyes of macaques and humans

Group-living primates frequently interact with each other to maintain social bonds as well as to compete for valuable resources. Observing such social interactions between group members provides individuals with essential information (e.g. on the fighting ability or altruistic attitude of group companions) to guide their social tactics and choice of social partners. This process requires individuals to selectively attend to the most informative content within a social scene. It is unclear how non-human primates allocate attention to social interactions in different contexts, and whether they share similar patterns of social attention to humans. Here we compared the gaze behaviour of rhesus macaques and humans when free-viewing the same set of naturalistic images. The images contained positive or negative social interactions between two conspecifics of different phylogenetic distance from the observer; i.e. affiliation or aggression exchanged by two humans, rhesus macaques, Barbary macaques, baboons or lions. Monkeys directed a variable amount of gaze at the two conspecific individuals in the images according to their roles in the interaction (i.e. giver or receiver of affiliation/aggression). Their gaze distribution to non-conspecific individuals was systematically varied according to the viewed species and the nature of interactions, suggesting a contribution of both prior experience and innate bias in guiding social attention. Furthermore, the monkeys’ gaze behavior was qualitatively similar to that of humans, especially when viewing negative interactions. Detailed analysis revealed that both species directed more gaze at the face than the body region when inspecting individuals, and attended more to the body region in negative than in positive social interactions. Our study suggests that monkeys and humans share a similar pattern of role-sensitive, species- and context-dependent social attention, implying a homologous cognitive mechanism of social attention between rhesus macaques and humans

Binary orbits as the driver of γ-ray emission and mass ejection in classical novae

Classical novae are the most common astrophysical thermonuclear explosions, occurring on the surfaces of white dwarf stars accreting gas from companions in binary star systems. Novae typically expel �10,000 solar masses of material at velocities exceeding 1,000 km/s. However, the mechanism of mass ejection in novae is poorly understood, and could be dominated by the impulsive flash of the thermonuclear runaway, prolonged optically thick winds, or binary interaction with the nova envelope. Classical novae are now routinely detected in GeV gamma-rays, suggesting that relativistic particles are accelerated by strong shocks in nova ejecta. Here we present high-resolution imaging of the gamma-ray-emitting nova V959 Mon at radio wavelengths, showing that its ejecta were shaped by binary motion: some gas was expelled rapidly along the poles as a wind from the white dwarf, while denser material drifted out along the equatorial plane, propelled by orbital motion. At the interface between the equatorial and polar regions, we observe synchrotron emission indicative of shocks and relativistic particle acceleration, thereby pinpointing the location of gamma-ray production. Binary shaping of the nova ejecta and associated internal shocks are expected to be widespread among novae, explaining why many novae are gamma-ray emitters

Grammatical evolution decision trees for detecting gene-gene interactions

<p>Abstract</p> <p>Background</p> <p>A fundamental goal of human genetics is the discovery of polymorphisms that predict common, complex diseases. It is hypothesized that complex diseases are due to a myriad of factors including environmental exposures and complex genetic risk models, including gene-gene interactions. Such epistatic models present an important analytical challenge, requiring that methods perform not only statistical modeling, but also variable selection to generate testable genetic model hypotheses. This challenge is amplified by recent advances in genotyping technology, as the number of potential predictor variables is rapidly increasing.</p> <p>Methods</p> <p>Decision trees are a highly successful, easily interpretable data-mining method that are typically optimized with a hierarchical model building approach, which limits their potential to identify interacting effects. To overcome this limitation, we utilize evolutionary computation, specifically grammatical evolution, to build decision trees to detect and model gene-gene interactions. In the current study, we introduce the Grammatical Evolution Decision Trees (GEDT) method and software and evaluate this approach on simulated data representing gene-gene interaction models of a range of effect sizes. We compare the performance of the method to a traditional decision tree algorithm and a random search approach and demonstrate the improved performance of the method to detect purely epistatic interactions.</p> <p>Results</p> <p>The results of our simulations demonstrate that GEDT has high power to detect even very moderate genetic risk models. GEDT has high power to detect interactions with and without main effects.</p> <p>Conclusions</p> <p>GEDT, while still in its initial stages of development, is a promising new approach for identifying gene-gene interactions in genetic association studies.</p

Decaying into the Hidden Sector

The existence of light hidden sectors is an exciting possibility that may be tested in the near future. If DM is allowed to decay into such a hidden sector through GUT suppressed operators, it can accommodate the recent cosmic ray observations without over-producing antiprotons or interfering with the attractive features of the thermal WIMP. Models of this kind are simple to construct, generic and evade all astrophysical bounds. We provide tools for constructing such models and present several distinct examples. The light hidden spectrum and DM couplings can be probed in the near future, by measuring astrophysical photon and neutrino fluxes. These indirect signatures are complimentary to the direct production signals, such as lepton jets, predicted by these models.Comment: 40 pages, 5 figure

Effective Dark Matter Model: Relic density, CDMS II, Fermi LAT and LHC

The Cryogenic Dark Matter Search recently announced the observation of two signal events with a 77% confidence level. Although statistically inconclusive, it is nevertheless suggestive. In this work we present a model-independent analysis on the implication of a positive signal in dark matter scattering off nuclei. Assuming the interaction between (scalar, fermion or vector) dark matter and the standard model induced by unknown new physics at the scale $\Lambda$, we examine various dimension-6 tree-level induced operators and constrain them using the current experimental data, e.g. the WMAP data of the relic abundance, CDMS II direct detection of the spin-independent scattering, and indirect detection data (Fermi LAT cosmic gamma-ray), etc. Finally, the LHC reach is also explored

A large ozone-circulation feedback and its implications for global warming assessments.

State-of-the-art climate models now include more climate processes which are simulated at higher spatial resolution than ever1. Nevertheless, some processes, such as atmospheric chemical feedbacks, are still computationally expensive and are often ignored in climate simulations1,2. Here we present evidence that how stratospheric ozone is represented in climate models can have a first order impact on estimates of effective climate sensitivity. Using a comprehensive atmosphere-ocean chemistry-climate model, we find an increase in global mean surface warming of around 1°C (~20%) after 75 years when ozone is prescribed at pre-industrial levels compared with when it is allowed to evolve self-consistently in response to an abrupt 4×CO2 forcing. The difference is primarily attributed to changes in longwave radiative feedbacks associated with circulation-driven decreases in tropical lower stratospheric ozone and related stratospheric water vapour and cirrus cloud changes. This has important implications for global model intercomparison studies1,2 in which participating models often use simplified treatments of atmospheric composition changes that are neither consistent with the specified greenhouse gas forcing scenario nor with the associated atmospheric circulation feedbacks3-5.We thank the European Research Council for funding through the ACCI project, project number 267760. The model development was part of the QESM-ESM project supported by the UK Natural Environment Research Council (NERC) under contract numbers RH/H10/19 and R8/H12/124. We acknowledge use of the MONSooN system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, which is a strategic partnership between the UK Met Office and NERC. A.C.M. acknowledges support from an AXA Postdoctoral Research Fellowship.This is the accepted manuscript. The final version is available from Nature Publishing at http://www.nature.com/nclimate/journal/v5/n1/full/nclimate2451.html