Steady-state free precession (SSFP) magnetic resonance imaging (MRI) can demonstrate details down to the cranial nerve (CN) level. High-resolution three-dimensional (3D) visualization can now quickly be performed at the workstation. However, we are still limited by visualization on flat screens. The emerging technologies in rapid prototyping or 3D printing overcome this limitation. It comprises a variety of automated manufacturing techniques, which use virtual 3D data sets to fabricate solid forms in a layer-by-layer technique. The complex neuroanatomy of the CNs may be better understood and depicted by the use of highly customizable advanced 3D printed models. In this technical note, after manually perfecting the segmentation of each CN and brain stem on each SSFP-MRI image, initial 3D reconstruction was performed. The bony skull base was also reconstructed from computed tomography (CT) data. Autodesk 3D Studio Max, available through freeware student/educator license, was used to three-dimensionally trace the 3D reconstructed CNs in order to create smooth graphically designed CNs and to assure proper fitting of the CNs into their respective neural foramina and fissures. This model was then 3D printed with polyamide through a commercial online service. Two different methods are discussed for the key segmentation and 3D reconstruction steps, by either using professional commercial software, i.e., Materialise Mimics, or utilizing a combination of the widely available software Adobe Photoshop, as well as a freeware software, OsiriX Lite.

This study examines the general relationships between crude oil consumption, real oil price and real GDP using a quarterly time series from 1993 to 2012. Specifically, the long‐term and short‐term GDP and price elasticities of oil consumption per capita were estimated using dynamic panel and pooled data regressions based on Nerlove's oil demand model for 25 countries that represent 75 per cent of global oil demand. Price elasticities were found for most OECD countries. These estimates were low and consistent with previous estimates. According to the study results, the short‐run price elasticity ranged between −0.05 and −0.20 and the long‐run between −0.11 and −0.36. Price elasticities for most non‐OECD countries were either positive or insignificant. Estimates of GDP elasticities varied. The short‐run GDP elasticity was between 0.15 and 1.09, while the long‐run was between 0.21 and 1.54. On average, income elasticity for OECD countries was found to be slightly higher than for non‐OECD countries. Contrary to expectations, we found China's income elasticity to be 0.34 in the short run, but it was 0.76 in the long run.

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In light of the ongoing growth in hedge fund and investment bank exposure in the NYMEX WTI crude oil futures market since the global financial crisis, we have applied linear causality tests to identify if each individual trader group in the disaggregated commitment of trader's report have prior destabilising effect on market return (the rate of change in crude oil prices), price volatility and the futures‐spot spread in the period 2009–2015. Consistent with the CFTC's disaggregated classification system, the trader groups considered are physical participants, swap dealers and money managers. In order to capture the nonlinear causality relationship, the Diks and Panchenko (Journal of Economic Dynamics and Control, 2006, 30, 1647) non‐parametric causality approach has also been utilised. Test results demonstrate that changes in the net positions of physical participants has both linear and nonlinear positive causality on expected market return, as well as feedback loops. Change in swap dealers net position, however, only have linear bidirectional causality with market return and futures‐spot spread, with unidirectional Granger causality with price volatility. While money managers were not price trend followers, they have preceding influence on market risk and return dynamics. It can be concluded that swap dealers and money managers have distortionary effect on market return, price volatility and the futures‐spot spread. Instead, Physical participants distortionary effect is restricted to market return.

This paper presents two approaches towards quantifying short‐term crude oil supply uncertainty. It provides some background information on the oil market and discusses different methods used in forecasting supply. Both approaches—semiquantitative (SQ) and Monte Carlo (MC)—are based on a risk matrix with likelihood and severity scores assigned. The result of the SQ approach is a risk band presented in percentage terms, whereas the MC method yields a probability distribution. The differences, advantages and disadvantages, as well as the potential expansions of both approaches are discussed. Both methods are applied to a set of major non‐OPEC oil producing countries, and the obtained results are compared.