The Dynamics of Energy-Grain Prices with Open Interest

This paper examines the short- and long-run daily relationships for a grain-energy nexus that includes the prices of corn, crude oil, ethanol, gasoline, soybeans, and sugar, and their open interest. The empirical results demonstrate the presence of these relationships in this nexus, and underscore the importance of ethanol and soybeans in all these relationships. In particular, ethanol and be considered as a catalyst in this nexus because of its significance as a loading factor, a long-run error corrector and a short-run adjuster. Ethanol leads all commodities in the price discovery process in the long run. The negative cross-price open interest effects suggest that there is a money outflow from all commodities in response to increases in open interest positions in the corn futures markets, indicating that active arbitrage activity takes place in those markets. On the other hand, an increase in the soybean open interest contributes to fund inflows in the corn futures market and the other futures markets, leading to more speculative activities in these markets. In connection with open interest, the ethanol market fails because of its thin market. Finally, it is interesting to note that the long-run equilibrium (cointegrating relationship), speeds of adjustment and open interest across markets have strengthened significantly during the 2009-2011 economic recovery period, compared with the full and 2007-2009 Great Recession periods.

The Dynamics of Energy-Grain Prices with Open Interest

This paper examines the short- and long-run daily relationships for a grain-energy nexus that includes the prices of corn, crude oil, ethanol, gasoline, soybeans, and sugar, and their open interest. The empirical results demonstrate the presence of these relationships in this nexus, and underscore the importance of ethanol and soybeans in all these relationships. In particular, ethanol and be considered as a catalyst in this nexus because of its significance as a loading factor, a long-run error corrector and a short-run adjuster. Ethanol leads all commodities in the price discovery process in the long run. The negative cross-price open interest effects suggest that there is a money outflow from all commodities in response to increases in open interest positions in the corn futures markets, indicating that active arbitrage activity takes place in those markets. On the other hand, an increase in the soybean open interest contributes to fund inflows in the corn futures market and the other futures markets, leading to more speculative activities in these markets. In connection with open interest, the ethanol market fails because of its thin market. Finally, it is interesting to note that the long-run equilibrium (cointegrating relationship), speeds of adjustment and open interest across markets have strengthened significantly during the 2009-2011 economic recovery period, compared with the full and 2007-2009 Great Recession periods

Identification of Enterococcus bacteria in gastrointestinal tract of dwarf honey bee, Apis florea Fabricius, 1973 (Hymenoptera: Apidae)

Apis species that engage in symbiotic association with Lactic Acid Bacteria (LAB), have diverse functions on their hosts. This study was intended to isolate and identify aeoccus bacteria living in the gastrointestinal tract of Asian dwarf honey bee, Apis florea,in Iran. One hundred isolates were Gram-stained and tested for catalase reaction. By using bacterial universal primers, the 16S rDNA gene of bacterial colonies was amplified. 16S rDNA genes from thirty bacteria were sequenced. Phylogenetic analysis showed that Enterococcus flora in the gastrointestinal tract of A. florea, contained five phenotypes which classified in the species E. faecium, E. faecalis and E. hirae.  Based on the specific association between bacteria and A. florea, we divided the Asian dwarf honey bee populations into four categories

Geometric morphometric approach on the sexual dimorphism of Cydia pomonella (Lep.: Tortricidae) in the North West of Iran

In order to study the sexual dimorphism of codling moth, Cydia pomonella (L.), nine geographical populations were collected from four provinces, East Azarbayjan, West Azarbayjan, Ardebil and Zandjan, in the North West of Iran in autumn 2003. By transforming the landmark geometric data into partial warp scores, 26 and 18 scores were obtained for the fore and hind wings, respectively. Relative warp analysis was performed and wings relative variations in two sexes were determined. Allometry test was carried out after estimating centroid size of individuals. Population-sex interaction was significant in two wings. To determine the contribution of uniform and non-uniform shape variables in explaining populations and sexes differences, MANOVA was performed separately for each type of variables. The result revealed that the non-uniform variables were more effective in determining sex differences in different populations especially in the hind wing. Simple analysis of variance (ANOVA) indicated that the centroid size of females was significantly greater than that of males. Allometry test revealed non significant association between centroid size and wing shape variations in males and females. RWA showed well discrimination between sexes, especially based on the hind wing landmarks. Overall shape deformation indicated wider basal part of wing in females compared with males especially in the hind wing

Fitness Varying Gravitational Constant in GSA

Gravitational Search Algorithm (GSA) is a recent metaheuristic algorithm inspired by Newton's law of gravity and law of motion. In this search process, position change is based on the calculation of step size which depends upon a constant namely, Gravitational Constant (G). G is an exponentially decreasing function throughout the search process. Further, inspite of having different masses, the value of G remains same for each agent, which may cause inappropriate step size of agents for the next move, and thus leads the swarm towards stagnation or sometimes skipping the true optima. To overcome stagnation, we first propose a gravitational constant having different scaling characteristics for different phase of the search process. Secondly, a dynamic behavior is introduced in this proposed gravitational constant which varies according to the fitness of the agents. Due to this behavior, the gravitational constant will be different for every agent based on its fitness and thus will help in controlling the acceleration and step sizes of the agents which further improve exploration and exploitation of the solution search space. The proposed strategy is tested over 23 well-known classical benchmark functions and 11 shifted and biased benchmark functions. Various statistical analyses and a comparative study with original GSA, Chaos-based GSA (CGSA), Bio-geography Based Optimization (BBO) and DBBO has been carried out