Does an environmental Kuznets curve for waste pollution exist in China?

China is an emerging and leading world economy. The pace of economic change has been tremendously rapid since the beginning of economic reforms. Despite the importance of the Environmental Kuznets Curve (EKC) and environmental problems in China, no previous study has tested the EKC in China because of the difficulty in obtaining data and the need to adjust the data. The focus of this paper is to test the EKC in China using province level data over the period 1992-2003. This study applies non-parametric techniques to estimate the relationship between income and the environmental quality of wastewater, air pollution and solid waste. Copyright © 2009 Inderscience Enterprises Ltd.

Environment and productivities in developed and developing countries : the case of carbon dioxide and sulfur dioxide

We propose a productivity index for undesirable outputs such as carbon dioxide (CO2) and sulfur dioxide (SO2) emissions and measure it using data from 51 developed and developing countries over the period 1971-2000. About half of the countries exhibit the productivity growth. The changes in the productivity index are linked with their respective per capita income using a semi-parametric model. Our results show technological catch up of low-income countries. However, overall productivities both of SO2 and CO2 show somewhat different results.

Productivity change of Nigerian insurance companies : 1994-2005

The aim of this paper is to estimate the productivity change of Nigerian insurance companies and to rank the companies analysed in the sample according to their productivity score. This benchmark exercise provides the companies analysed with a view of how their relative productivity can be upgraded. For this purpose, the non-parametric Luenberger productivity model is used. For comparative purposes, the non-parametric Luenberger-Hicks-Moorsteen productivity indicator is also used. The companies are ranked according to their total productivity for the period 1994-2005, using both models, which produce variations in the respective results. Economic implications arising from the study are derived.

Can larger cemented femoral components reduce periprosthetic fractures?

Introduction The risk for late periprosthetic fractures is higher in patients treated for a neck of femur fracture compared to those treated for osteoarthritis. It has been hypothesised that osteopenia and consequent decreased stiffness of the proximal femur are responsible for this. We investigated if a femoral component with a bigger body would increase the torque to failure in a biaxially loaded composite sawbone model. Method A biomechanical composite sawbone model was used. Two different body sizes (Exeter 44-1 vs 44-4) of a polished tapered cemented stem were implanted by an experienced surgeon, in 7 sawbones each and loaded at 40 deg/s internal rotation until failure. Torque to fracture and fracture energy were measured using a biaxial materials testing device (Instron 8874). Data are non-parametric and tested with Mann-Whitney U-test. Results The mean torque load to fracture was 154.1 NM (SD 4.4) for the 44-1 stem and 229 NM (SD10.9) for the 44-4 stem (p = 0.01). The mean fracture energy was 9.6 J (SD1.2) for the 44-1 stem and 17.2 J (SD2.0) for the 44-4 stem (p = 0.14). Conclusion the use of a large body polished tapered cemented stem for neck of femur fractures increases the torque to failure in a biomechanical model and therefore is likely to reduce late periprosthetic fracture risk in this vulnerable cohort.

Bayesian hierarchical models for analysing spatial point-based data at a grid level: A comparison of approaches

Spatial data are now prevalent in a wide range of fields including environmental and health science. This has led to the development of a range of approaches for analysing patterns in these data. In this paper, we compare several Bayesian hierarchical models for analysing point-based data based on the discretization of the study region, resulting in grid-based spatial data. The approaches considered include two parametric models and a semiparametric model. We highlight the methodology and computation for each approach. Two simulation studies are undertaken to compare the performance of these models for various structures of simulated point-based data which resemble environmental data. A case study of a real dataset is also conducted to demonstrate a practical application of the modelling approaches. Goodness-of-fit statistics are computed to compare estimates of the intensity functions. The deviance information criterion is also considered as an alternative model evaluation criterion. The results suggest that the adaptive Gaussian Markov random field model performs well for highly sparse point-based data where there are large variations or clustering across the space; whereas the discretized log Gaussian Cox process produces good fit in dense and clustered point-based data. One should generally consider the nature and structure of the point-based data in order to choose the appropriate method in modelling a discretized spatial point-based data.

The impact of mobile phone distraction on the braking behaviour of young drivers : a hazard-based duration model

Braking is a crucial driving task with a direct relationship with crash risk, as both excess and inadequate braking can lead to collisions. The objective of this study was to compare the braking profile of young drivers distracted by mobile phone conversations to non-distracted braking. In particular, the braking behaviour of drivers in response to a pedestrian entering a zebra crossing was examined using the CARRS-Q Advanced Driving Simulator. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free, and handheld. In addition to driving the simulator, each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The drivers were 18–26 years old and split evenly by gender. A linear mixed model analysis of braking profiles along the roadway before the pedestrian crossing revealed comparatively increased decelerations among distracted drivers, particularly during the initial 20 kph of deceleration. Drivers’ initial 20 kph deceleration time was modelled using a parametric accelerated failure time (AFT) hazard-based duration model with a Weibull distribution with clustered heterogeneity to account for the repeated measures experiment design. Factors found to significantly influence the braking task included vehicle dynamics variables like initial speed and maximum deceleration, phone condition, and driver-specific variables such as licence type, crash involvement history, and self-reported experience of using a mobile phone whilst driving. Distracted drivers on average appear to reduce the speed of their vehicle faster and more abruptly than non-distracted drivers, exhibiting excess braking comparatively and revealing perhaps risk compensation. The braking appears to be more aggressive for distracted drivers with provisional licenses compared to drivers with open licenses. Abrupt or excessive braking by distracted drivers might pose significant safety concerns to following vehicles in a traffic stream.

Experimental and numerical study of polymeric foam efficacy in portable water filled barriers

Portable, water filled road safety barriers are used to provide protection and reduce the potential hazard due to errant vehicles in areas where the road conditions change frequently (e.g. near road work sites). As part of an effort to reduce excessive working widths typical of these systems, a study was conducted to assess the effectiveness of introducing polymeric foam filled panels into the design. Surrogate impact tests of a design typical of such as barrier system were conducted utilising a pneumatically powered horizontal impact testing machine up to impact energies of 7.40 kJ. Results of these tests are utilised to examine the barrier behaviour, in addition to being used to validate a couple FE/SPH model of the barrier system. Once validated, the FE/SPH model it utilised as the basis for a parametric study into the efficacy and effects of the inclusion of polymeric foam filled panels on the performance of portable water filled road safety barriers. It was found that extruded polystyrene foam functioned well, with a greater thickness of the foam panel significantly reducing the impacting body velocity as the barrier began to translate.

Effective diffusivity and evaporative cooling in convective drying of food material

This article presents mathematical models to simulate coupled heat and mass transfer during convective drying of food materials using three different effective diffusivities: shrinkage dependent, temperature dependent and average of those two. Engineering simulation software COMSOL Multiphysics was utilized to simulate the model in 2D and 3D. The simulation results were compared with experimental data. It is found that the temperature dependent effective diffusivity model predicts the moisture content more accurately at the initial stage of the drying, whereas, the shrinkage dependent effective diffusivity model is better for the final stage of the drying. The model with shrinkage dependent effective diffusivity shows evaporative cooling phenomena at the initial stage of drying. This phenomenon was investigated and explained. Three dimensional temperature and moisture profiles show that even when the surface is dry, inside of the sample may still contain large amount of moisture. Therefore, drying process should be carefully dealt with otherwise microbial spoilage may start from the centre of the ‘dried’ food. A parametric investigation has been conducted after the validation of the model.

Cerebellar grey-matter deficits, cannabis use and first-episode schizophrenia in adolescents and young adults

Epidemiological data link adolescent cannabis use to psychosis and schizophrenia, but its contribution to schizophrenia neuropathology remains controversial. First-episode schizophrenia (FES) patients show regional cerebral grey- and white-matter changes as well as a distinct pattern of regional grey-matter loss in the vermis of the cerebellum. The cerebellum possesses a high density of cannabinoid type 1 receptors involved in the neuronal diversification of the developing brain. Cannabis abuse may interfere with this process during adolescent brain maturation leading to ‘schizophrenia-like’ cerebellar pathology. Magnetic resonance imaging and cortical pattern matching techniques were used to investigate cerebellar grey and white matter in FES patients with and without a history of cannabis use and non-psychiatric cannabis users. In the latter group we found lifetime dose-dependent regional reduction of grey matter in the right cerebellar lobules and a tendency for more profound grey-matter reduction in lobule III with younger age at onset of cannabis use. The overall regional grey-matter differences in cannabis users were within the normal variability of grey-matter distribution. By contrast, FES subjects had lower total cerebellar grey-matter : total cerebellar volume ratio and marked grey-matter loss in the vermis, pedunculi, flocculi and lobules compared to pair-wise matched healthy control subjects. This pattern and degree of grey-matter loss did not differ from age-matched FES subjects with comorbid cannabis use. Our findings indicate small dose-dependent effects of juvenile cannabis use on cerebellar neuropathology but no evidence of an additional effect of cannabis use on FES cerebellar grey-matter pathology.

Simulation-based density estimation for time series using covariate data

This paper proposes a simulation-based density estimation technique for time series that exploits information found in covariate data. The method can be paired with a large range of parametric models used in time series estimation. We derive asymptotic properties of the estimator and illustrate attractive finite sample properties for a range of well-known econometric and financial applications.

Adaptive estimation of hidden semi-Markov chains with parameterised transition probabilities and exponential decaying states

This paper develops maximum likelihood (ML) estimation schemes for finite-state semi-Markov chains in white Gaussian noise. We assume that the semi-Markov chain is characterised by transition probabilities of known parametric from with unknown parameters. We reformulate this hidden semi-Markov model (HSM) problem in the scalar case as a two-vector homogeneous hidden Markov model (HMM) problem in which the state consist of the signal augmented by the time to last transition. With this reformulation we apply the expectation Maximumisation (EM ) algorithm to obtain ML estimates of the transition probabilities parameters, Markov state levels and noise variance. To demonstrate our proposed schemes, motivated by neuro-biological applications, we use a damped sinusoidal parameterised function for the transition probabilities.

Complementary surface-enhanced resonance raman spectroscopic biodetection of mixed protein solutions by chitosan- and silica-coated plasmon-tuned silver nanoparticles

Silver nanoparticles with identical plasmonic properties but different surface functionalities are synthesized and tested as chemically selective surface-enhanced resonance Raman (SERR) amplifiers in a two-component protein solution. The surface plasmon resonances of the particles are tuned to 413 nm to match the molecular resonance of protein heme cofactors. Biocompatible functionalization of the nanoparticles with a thin film of chitosan yields selective SERR enhancement of the anionic protein cytochrome b5, whereas functionalization with SiO2 amplifies only the spectra of the cationic protein cytochrome c. As a result, subsequent addition of the two differently functionalized particles yields complementary information on the same mixed protein sample solution. Finally, the applicability of chitosan-coated Ag nanoparticles for protein separation was tested by in situ resonance Raman spectroscopy.

Tailored silica coated Ag nanoparticles for non-invasive surface enhanced Raman spectroscopy of biomolecular targets

Silica coated Ag nanoparticles with defined surface plasmon resonances are used to selectively detect and analyze protein cofactors in solution and on interfaces via surface enhanced resonance Raman spectroscopy. The silica coating has a surprisingly small effect on optical amplification but minimizes unwanted interactions between the protein and the nanoparticle.

Functionalized Ag nanoparticles with tunable optical properties for selective protein analysis

We present a preparation procedure for small sized biocompatibly coated Ag nanoparticles with tunable surface plasmon resonances. The conditions were optimised with respect to the resonance Raman signal enhancement of heme proteins and to the preservation of the native protein structure....

Experimental study of load-bearing cold-formed steel walls exposed to realistic design fires

This paper presents the details of full scale fire tests of LSF wall panels conducted using realistic fire time-temperature curves. Tests included eight LSF wall specimens of various configurations exposed to both parametric design and natural fire curves. Details of the fire test set-up, test procedure and the results including the measured time-temperature and deformation curves of LSF wall panels are presented along with wall stud failure modes and times. This paper also compares the structural and thermal behavioural characteristics of LSF wall studs with those based on the standard time-temperature curve. Finally, the stud failure times and temperatures are summarized for both standard and realistic design fire curves. This study provides the necessary test data to validate the numerical models of LSF wall panels and to undertake a detailed study into the structural and thermal performance of LSF wall panels exposed to realistic design fire curves.