Common and Fundamental Factors in Stock Returns of Canadian Oil and Gas Companies

In this paper, we assess the determinants of Canadian oil and gas stocks returns. We find that the stock return of Canadian energy stock is positively associated with returns on the Canadian stock market, appreciations of crude oil and natural gas prices, growth in internal cash flows and proven reserves, and negatively with interest rates. Surprisingly, however, production volume and a weakening of the Canadian dollar against the U.S. dollar have a negative impact. This latter impact is more pronounced for oil producers than for integrated energy companies. Finally, we find that the influence of the exchange rate, the market return and prices of natural gas on Canadian oil and gas stocks changes significantly over the years 1995-1998 and 2000-2002. Le but de cet article est de mesurer ce qui influence le rendement des actions d'entreprises pétrolières et gazières canadiennes. Nous trouvons que le rendement des actions de ces entreprises énergétiques est influencé positivement par le rendement du marché canadien dans son ensemble, par une appréciation du prix du pétrole et du gaz naturel, par une croissance dans les flux monétaires discrétionnaires de l'entreprise, par la quantité de réserves prouvées de l'entreprise. Nous trouvons également que le volume de production et une dépréciation du dollar canadien par rapport à la devise américaine réduit sensiblement le rendement des titres énergétiques, ce qui va à l'encontre de notre hypothèse initiale. L'impact du taux de change est encore plus marqué pour les producteurs indépendants que pour les entreprises intégrées. En dernier lieu, nous montrons que le marché a subi une cassure significative entre les années 1995-1998 et 2000-2002, spécialement pour ce qui est de l'impact du taux de change, du rendement de marché et du pris du gaz naturel.stock return valuation, panel data analysis, oil and gas industry, rendement des actions, analyse de données transversales, industrie pétrolière et gazière

Non-Equilibrium Surface Tension of the Vapour-Liquid Interface of Active Lennard-Jones Particles

We study a three-dimensional system of self-propelled Brownian particles interacting via the Lennard-Jones potential. Using Brownian Dynamics simulations in an elongated simulation box, we investigate the steady states of vapour-liquid phase coexistence of active Lennard-Jones particles with planar interfaces. We measure the normal and tangential components of the pressure tensor along the direction perpendicular to the interface and verify mechanical equilibrium of the two coexisting phases. In addition, we determine the non-equilibrium interfacial tension by integrating the difference of the normal and tangential component of the pressure tensor, and show that the surface tension as a function of strength of particle attractions is well-fitted by simple power laws. Finally, we measure the interfacial stiffness using capillary wave theory and the equipartition theorem, and find a simple linear relation between surface tension and interfacial stiffness with a proportionality constant characterized by an effective temperature.Comment: 12 pages, 5 figures (Corrected typos and References

Crystallization in suspensions of hard spheres: A Monte Carlo and Molecular Dynamics simulation study

The crystallization of a metastable melt is one of the most important non equilibrium phenomena in condensed matter physics, and hard sphere colloidal model systems have been used for several decades to investigate this process by experimental observation and computer simulation. Nevertheless, there is still an unexplained discrepancy between simulation data and experimental nucleation rate densities. In this paper we examine the nucleation process in hard spheres using molecular dynamics and Monte Carlo simulation. We show that the crystallization process is mediated by precursors of low orientational bond-order and that our simulation data fairly match the experimental data sets

Elastomeric Osteoconductive Synthetic Scaffolds with Acquired Osteoinductivity Expedite the Repair of Critical Femoral Defects in Rats

Regenerative medicine aspires to reduce reliance on or overcome limitations associated with donor tissue-mediated repair. Structural bone allografts are commonly used in orthopedic surgery, with a high percentage of graft failure due to poor tissue integration. This problem is aggravated among elderly, those suffering from metabolic conditions, or those undergoing cancer therapies that compromise graft healing. Toward this end, we developed a synthetic graft named FlexBone, in which nanocrystalline hydroxyapatite (50-wt%) was structurally integrated with crosslinked poly(hydroxyethyl methacrylate) hydrogel, which provides dimensional stability and elasticity. It recapitulates the essential role of nanocrystalline hydroxyapatite in defining the osteoconductivity and biochemical microenvironment of bone because of its affinity for biomolecules. Here, we demonstrate that FlexBone effectively absorbed endogenously secreted signaling molecules associated with the inflammation/graft healing cascade upon being press-fit into a 5-mm rat femoral segmental defect. Further, when preabsorbed with a single dose of 400-ng recombinant human (rh) bone morphogenetic protein-2/7 heterodimer, it enabled the functional repair of the critical-sized defect by 8-12 weeks. FlexBone was stably encapsulated by the bridging bony callus and the FlexBone-callus interface was continuously remodeled. In summary, FlexBone combines the dimensional stability and osteoconductivity of structural bone allografts with desirable surgical compressibility and acquired osteoinductivity in an easy-to-fabricate and scalable synthetic biomaterial.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90480/1/ten-2Etea-2E2010-2E0274.pd

Orbital and spin physics in LiNiO2 and NaNiO2

We derive a spin-orbital Hamiltonian for a triangular lattice of e_g orbital degenerate (Ni^{3+}) transition metal ions interacting via 90 degree superexchange involving (O^{2-}) anions, taking into account the on-site Coulomb interactions on both the anions and the transition metal ions. The derived interactions in the spin-orbital model are strongly frustrated, with the strongest orbital interactions selecting different orbitals for pairs of Ni ions along the three different lattice directions. In the orbital ordered phase, favoured in mean field theory, the spin-orbital interaction can play an important role by breaking the U(1) symmetry generated by the much stronger orbital interaction and restoring the threefold symmetry of the lattice. As a result the effective magnetic exchange is non-uniform and includes both ferromagnetic and antiferromagnetic spin interactions. Since ferromagnetic interactions still dominate, this offers yet insufficient explanation for the absence of magnetic order and the low-temperature behaviour of the magnetic susceptibility of stoichiometric LiNiO_2. The scenario proposed to explain the observed difference in the physical properties of LiNiO_2 and NaNiO_2 includes small covalency of Ni-O-Li-O-Ni bonds inducing weaker interplane superexchange in LiNiO_2, insufficient to stabilize orbital long-range order in the presence of stronger intraplane competition between superexchange and Jahn-Teller coupling.Comment: 33 pages, 12 postscript figures, uses iopams.sty . This article features in New Journal of Physics as part of a Focus Issue on Orbital Physics - all contributions may be freely accessed at (http://stacks.iop.org/1367-2630/6/i=1/a=E05). The published version of this article may be found at http://stacks.iop.org/1367-2630/7/12

Scalable Functional Bone Substitutes: Strategic Integration of Key Structural Elements of Bone in Synthetic Biomaterials

Summary: Introduces recent advances in the evolvement of non-metallic orthopedic biomaterials in the design of organic-inorganic composite bone substitutes

Improving the prediction of glassy dynamics by pinpointing the local cage

The relationship between structure and dynamics in glassy fluids remains an intriguing open question. Recent work has shown impressive advances in our ability to predict local dynamics using structural features, most notably due to the use of advanced machine learning techniques. Here we explore whether a simple linear regression algorithm combined with intelligently chosen structural order parameters can reach the accuracy of the current, most advanced machine learning approaches for predicting dynamic propensity. To do this we introduce a method to pinpoint the cage state of the initial configuration -- i.e. the configuration consisting of the average particle positions when particle rearrangement is forbidden. We find that, in comparison to both the initial state and the inherent state, the structure of the cage state is highly predictive of the long-time dynamics of the system. Moreover, by combining the cage state information with the initial state, we are able to predict dynamic propensities with unprecedentedly high accuracy over a broad regime of time scales, including the caging regime