Growth and public infrastructure

The paper analyzes a multicountry extension of the Barro model of productive public expenditure. In the presence of positive infrastructural externalities between countries, the provision of infrastructure will be inefficiently low if countries do not coordinate. This provides a role for a supranational body, such as the European Union, to coordinate the policies of the individual governments. It is shown how intervention by a supranational body can raise welfare by internalizing the infrastructural externality. Infrastructural externalities increase the importance of tax policy in the growth process and distribute the benefits of taxation across countries.

Using Doppler radar with a simple explicit microphysics model to diagnose problems with ice sublimation depth-scales in forecast models

Several previous studies have attempted to assess the sublimation depth-scales of ice particles from clouds into clear air. Upon examining the sublimation depth-scales in the Met Office Unified Model (MetUM), it was found that the MetUM has evaporation depth-scales 2–3 times larger than radar observations. Similar results can be seen in the European Centre for Medium-Range Weather Forecasts (ECMWF), Regional Atmospheric Climate Model (RACMO) and Météo-France models. In this study, we use radar simulation (converting model variables into radar observations) and one-dimensional explicit microphysics numerical modelling to test and diagnose the cause of the deep sublimation depth-scales in the forecast model. The MetUM data and parametrization scheme are used to predict terminal velocity, which can be compared with the observed Doppler velocity. This can then be used to test the hypothesis as to why the sublimation depth-scale is too large within the MetUM. Turbulence could lead to dry air entrainment and higher evaporation rates; particle density may be wrong, particle capacitance may be too high and lead to incorrect evaporation rates or the humidity within the sublimating layer may be incorrectly represented. We show that the most likely cause of deep sublimation zones is an incorrect representation of model humidity in the layer. This is tested further by using a one-dimensional explicit microphysics model, which tests the sensitivity of ice sublimation to key atmospheric variables and is capable of including sonde and radar measurements to simulate real cases. Results suggest that the MetUM grid resolution at ice cloud altitudes is not sufficient enough to maintain the sharp drop in humidity that is observed in the sublimation zone.

Selection of funding schemes by a borrowing decision model: a Hong Kong case study

In financial decision-making, a number of mathematical models have been developed for financial management in construction. However, optimizing both qualitative and quantitative factors and the semi-structured nature of construction finance optimization problems are key challenges in solving construction finance decisions. The selection of funding schemes by a modified construction loan acquisition model is solved by an adaptive genetic algorithm (AGA) approach. The basic objectives of the model are to optimize the loan and to minimize the interest payments for all projects. Multiple projects being undertaken by a medium-size construction firm in Hong Kong were used as a real case study to demonstrate the application of the model to the borrowing decision problems. A compromise monthly borrowing schedule was finally achieved. The results indicate that Small and Medium Enterprise (SME) Loan Guarantee Scheme (SGS) was first identified as the source of external financing. Selection of sources of funding can then be made to avoid the possibility of financial problems in the firm by classifying qualitative factors into external, interactive and internal types and taking additional qualitative factors including sovereignty, credit ability and networking into consideration. Thus a more accurate, objective and reliable borrowing decision can be provided for the decision-maker to analyse the financial options.

Sensitivity analysis of a cyanobacterial growth and movement model under two different flow regimes

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling cyanobacterial behaviour in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes, reservoirs and rivers. A new deterministic–mathematical model was developed, which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the major factors that affect the cyanobacterial bloom formation in rivers including light, nutrients and temperature. A parameter sensitivity analysis using a one-at-a-time approach was carried out. There were two objectives of the sensitivity analysis presented in this paper: to identify the key parameters controlling the growth and movement patterns of cyanobacteria and to provide a means for model validation. The result of the analysis suggested that maximum growth rate and day length period were the most significant parameters in determining the population growth and colony depth, respectively.

The automatic layout model in the sequencing of construction activities of multi-objective diaphragm wall unit by using self-learning neural network

Foundation construction process has been an important key point in a successful construction engineering. The frequency of using diaphragm wall construction method among many deep excavation construction methods in Taiwan is the highest in the world. The traditional view of managing diaphragm wall unit in the sequencing of construction activities is to establish each phase of the sequencing of construction activities by heuristics. However, it conflicts final phase of engineering construction with unit construction and effects planning construction time. In order to avoid this kind of situation, we use management of science in the study of diaphragm wall unit construction to formulate multi-objective combinational optimization problem. Because the characteristic (belong to NP-Complete problem) of problem mathematic model is multi-objective and combining explosive, it is advised that using the 2-type Self-Learning Neural Network (SLNN) to solve the N=12, 24, 36 of diaphragm wall unit in the sequencing of construction activities program problem. In order to compare the liability of the results, this study will use random researching method in comparison with the SLNN. It is found that the testing result of SLNN is superior to random researching method in whether solution-quality or Solving-efficiency.

Motivation, rationale and key results from the GERBILS Saharan dust measurement campaign

The Geostationary Earth Radiation Budget Intercomparison of Longwave and Shortwave radiation (GERBILS) was an observational field experiment over North Africa during June 2007. The campaign involved 10 flights by the FAAM BAe-146 research aircraft over southwestern parts of the Sahara Desert and coastal stretches of the Atlantic Ocean. Objectives of the GERBILS campaign included characterisation of mineral dust geographic distribution and physical and optical properties, assessment of the impact upon radiation, validation of satellite remote sensing retrievals, and validation of numerical weather prediction model forecasts of aerosol optical depths (AODs) and size distributions. We provide the motivation behind GERBILS and the experimental design and report the progress made in each of the objectives. We show that mineral dust in the region is relatively non-absorbing (mean single scattering albedo at 550 nm of 0.97) owing to the relatively small fraction of iron oxides present (1–3%), and that detailed spectral radiances are most accurately modelled using irregularly shaped particles. Satellite retrievals over bright desert surfaces are challenging owing to the lack of spectral contrast between the dust and the underlying surface. However, new techniques have been developed which are shown to be in relatively good agreement with AERONET estimates of AOD and with each other. This encouraging result enables relatively robust validation of numerical models which treat the production, transport, and deposition of mineral dust. The dust models themselves are able to represent large-scale synoptically driven dust events to a reasonable degree, but some deficiencies remain both in the Sahara and over the Sahelian region, where cold pool outflow from convective cells associated with the intertropical convergence zone can lead to significant dust production.

Comparing a discrete and continuum model of the intestinal crypt

The integration of processes at different scales is a key problem in the modelling of cell populations. Owing to increased computational resources and the accumulation of data at the cellular and subcellular scales, the use of discrete, cell-level models, which are typically solved using numerical simulations, has become prominent. One of the merits of this approach is that important biological factors, such as cell heterogeneity and noise, can be easily incorporated. However, it can be difficult to efficiently draw generalizations from the simulation results, as, often, many simulation runs are required to investigate model behaviour in typically large parameter spaces. In some cases, discrete cell-level models can be coarse-grained, yielding continuum models whose analysis can lead to the development of insight into the underlying simulations. In this paper we apply such an approach to the case of a discrete model of cell dynamics in the intestinal crypt. An analysis of the resulting continuum model demonstrates that there is a limited region of parameter space within which steady-state (and hence biologically realistic) solutions exist. Continuum model predictions show good agreement with corresponding results from the underlying simulations and experimental data taken from murine intestinal crypts.

Limitations of the MRL mouse as a model for cardiac regeneration

Objective Myocardial repair following injury in mammals is restricted such that damaged areas are replaced by scar tissue, impairing cardiac function. MRL mice exhibit exceptional regenerative healing in an ear punch wound model. Some myocardial repair with restoration of heart function has also been reported following cryoinjury. Increased cardiomyocyte proliferation and a foetal liver stem cell population were implicated. We investigated molecular mechanisms facilitating myocardial repair in MRL mice to identify potential therapeutic targets in non-regenerative species. Methods Expressions of specific cell-cycle regulators that might account for regeneration (CDKs 1, 2, 4 and 6; cyclins A, E, D1 and B1; p21, p27 and E2F5) were compared by immunoblotting in MRL and control C57BL/6 ventricles during development. Flow cytometry was used to investigate stem cell populations in livers from foetal mice, and infarct sizes were compared in coronary artery-ligated and sham-treated MRL and C57BL/6 adult mice. Key findings No differences in the expressions of cell cycle regulators were observed between the two strains. Expressions of CD34+Sca1+ckit-, CD34+Sca1+ckit+ and CD34+Sca1-ckit+ increased in livers from C57BL/6 vs MRL mice. No differences were observed in infarct sizes, levels of fibrosis, Ki67 staining or cardiac function between MRL and C57BL/6 mice. Conclusions No intrinsic differences were observed in cell cycle control molecules or stem cell populations between MRL and control C57BL mouse hearts. Pathophysiologically relevant ischaemic injury is not repaired more efficiently in MRL myocardium, questioning the use of the MRL mouse as a reliable model for cardiac regeneration in response to pathophysiologically relevant forms of injury.

An ECOOP web portal for visualising and comparing distributed coastal oceanography model and in situ data

As part of a large European coastal operational oceanography project (ECOOP), we have developed a web portal for the display and comparison of model and in situ marine data. The distributed model and in situ datasets are accessed via an Open Geospatial Consortium Web Map Service (WMS) and Web Feature Service (WFS) respectively. These services were developed independently and readily integrated for the purposes of the ECOOP project, illustrating the ease of interoperability resulting from adherence to international standards. The key feature of the portal is the ability to display co-plotted timeseries of the in situ and model data and the quantification of misfits between the two. By using standards-based web technology we allow the user to quickly and easily explore over twenty model data feeds and compare these with dozens of in situ data feeds without being concerned with the low level details of differing file formats or the physical location of the data. Scientific and operational benefits to this work include model validation, quality control of observations, data assimilation and decision support in near real time. In these areas it is essential to be able to bring different data streams together from often disparate locations.

Glucokinase Regulatory Protein genetic variant interacts with omega-3 PUFA to influence insulin resistance and inflammation in metabolic syndrome

Glucokinase Regulatory Protein (GCKR) plays a central role regulating both hepatic triglyceride and glucose metabolism. Fatty acids are key metabolic regulators, which interact with genetic factors and influence glucose metabolism and other metabolic traits. Omega-3 polyunsaturated fatty acids (n-3 PUFA) have been of considerable interest, due to their potential to reduce metabolic syndrome (MetS) risk. Objective To examine whether genetic variability at the GCKR gene locus was associated with the degree of insulin resistance, plasma concentrations of C-reactive protein (CRP) and n-3 PUFA in MetS subjects. Design Homeostasis model assessment of insulin resistance (HOMA-IR), HOMA-B, plasma concentrations of C-peptide, CRP, fatty acid composition and the GCKR rs1260326-P446L polymorphism, were determined in a cross-sectional analysis of 379 subjects with MetS participating in the LIPGENE dietary cohort. Results Among subjects with n-3 PUFA levels below the population median, carriers of the common C/C genotype had higher plasma concentrations of fasting insulin (P = 0.019), C-peptide (P = 0.004), HOMA-IR (P = 0.008) and CRP (P = 0.032) as compared with subjects carrying the minor T-allele (Leu446). In contrast, homozygous C/C carriers with n-3 PUFA levels above the median showed lower plasma concentrations of fasting insulin, peptide C, HOMA-IR and CRP, as compared with individuals with the T-allele. Conclusions We have demonstrated a significant interaction between the GCKR rs1260326-P446L polymorphism and plasma n-3 PUFA levels modulating insulin resistance and inflammatory markers in MetS subjects. Further studies are needed to confirm this gene-diet interaction in the general population and whether targeted dietary recommendations can prevent MetS in genetically susceptible individuals.

Exploring behavioural change through an agent-oriented system dynamics model: the use of personal protective equipment among pesticide applicators in Colombia

The misuse of Personal Protective Equipment results in health risk among smallholders in developing countries, and education is often proposed to promote safer practices. However, evidence point to limited effects of education. This paper presents a System Dynamics model which allows the identification of risk-minimizing policies for behavioural change. The model is based on the IAC framework and survey data. It represents farmers' decision-making from an agent-oriented standpoint. The most successful intervention strategy was the one which intervened in the long term, targeted key stocks in the systems and was diversified. However, the results suggest that, under these conditions, no policy is able to trigger a self sustaining behavioural change. Two implementation approaches were suggested by experts. One, based on constant social control, corresponds to a change of the current model's parameters. The other, based on participation, would lead farmers to new thinking, i.e. changes in their decision-making structure.

Pollination ecology in the 21st century: key questions for future research

To inspire new ideas in research on pollination ecology, we list the most important unanswered questions in the field. This list was drawn up by contacting 170 scientists from different areas of pollination ecology and asking them to contribute their opinion on the greatest knowledge gaps that need to be addressed. Almost 40% of them took part in our email poll and we received more than 650 questions and comments, which we classified into different categories representing various aspects of pollination research. The original questions were merged and synthesised, and a final vote and ranking led to the resultant list. The categories cover plant sexual reproduction, pollen and stigma biology, abiotic pollination, evolution of animal-mediated pollination, interactions of pollinators and floral antagonists, pollinator behaviour, taxonomy, plant-pollinator assemblages, geographical trends in diversity, drivers of pollinator loss, ecosystem services, management of pollination, and conservation issues such as the implementation of pollinator conservation. We focused on questions that were of a broad scope rather than case-specific; thus, addressing some questions may not be feasible within single research projects but constitute a general guide for future directions. With this compilation we hope to raise awareness of pollination-related topics not only among researchers but also among non-specialists including policy makers, funding agencies and the public at large.