Price competition between a macrocell and a small-cell service provider with limited resources and optimal bandwidth user subscription: a game-theoretical model

The ever-increasing demand for higher data rates in wireless commutations provides a rationale for small cells deployment. While the physical and technological aspects of small-cell networks have been extensively studied in recent years, the economic analysis has received much less attention. We focus on the economic rationale for a small-cell service provider (SSP) operating a market where an incumbent macrocell service provider (MSP) exists, and competition develops. We analyze such scenario for the case of fixed users by means of Game Theory, specifically through a two-stage game: in the first stage each service provider posts its price according to a Stackelberg game where the MSP is the leader and the SSP is the follower; and, in the second stage, each user chooses both which provider to subscribe to and the optimal amount of bandwidth. A subgame perfect Nash equilibrium is used as a solution concept, and it is derived analytically. We show that the SSP has an incentive to operate in the market and its profit gets higher as SSP’s resources increase. Furthermore, users benefit from SSP’s operation, which may provide a rationale for a regulatory authority to grant the SSP access to the market, despite the fact that MSP’s profit is harmed. Finally, we identify two modes of operation of the system, which depend on the SSP coverage: one where SSP’s deployment is limited and the MSP strategy is not affected by SSP competition and takes only the users outside the SSP coverage; and another, where the SSP covers a large area and the MSP competes against the SSP taking a fraction of the users inside the small cells.     

An ecosystemic approach for assessing the urban water self-sufficiency potential: lessons from the Mediterranean

Frequent water stress episodes affecting urban hubs have caused a shift in urban water management towards integrated approaches and motivated a search for alternative water resources. Large-scale rainwater harvesting on the municipal scale can overcome the disadvantages of climate dependence and the volume restrictions associated with small-scale collection facilities. In this paper, two tools based on the urban metabolism concept are used to determine the water self-sufficiency potential of urban systems from urban runoff: a simple water self-sufficiency potential indicator and a socioeconomic water flow accounting scheme, which includes water losses. Both tools are applied to a densely populated coastal area that exemplifies urban centres in the Mediterranean. This approach is useful for regions with restricted data availability on water use and facilitates information dissemination to policy makers. The results indicate a significant water self-sufficiency potential for the area of study, even under projections of reduced precipitation in the area.     

Robustness of optimal channel reservation using handover prediction in multiservice wireless networks

The aim of our study is to obtain theoretical limits for the gain that can be expected when using handover prediction and to determine the sensitivity of the system performance against different parameters. We apply an average-reward reinforcement learning approach based on afterstates to the design of optimal admission control policies in mobile multimedia cellular networks where predictive information related to the occurrence of future handovers is available. We consider a type of predictor that labels active mobile terminals in the cell neighborhood a fixed amount of time before handovers are predicted to occur, which we call the anticipation time. The admission controller exploits this information to reserve resources efficiently. We show that there exists an optimum value for the anticipation time at which the highest performance gain is obtained. Although the optimum anticipation time depends on system parameters, we find that its value changes very little when the system parameters vary within a reasonable range. We also find that, in terms of system performance, deploying prediction is always advantageous when compared to a system without prediction, even when the system parameters are estimated with poor precision.     

Different bacterial models for in vitro induction of non‐cavitated enamel caries‐like lesions: Microhardness and polarized light miscroscopy analyses

The aim of this study was to compare different bacterial models for in vitro induction of non‐cavitated enamel caries‐like lesions by microhardness and polarized light microscopy analyses. One hundred blocks of bovine enamel were randomly divided into four groups (n = 25) according to the bacterial model for caries induction: (A) Streptococcus mutans, (B) S. mutans and Lactobacillus acidophilus, (C) S. mutans and L. casei, and (D) S. mutans, L. acidophilus, and L. casei. Within each group, the blocks were randomly divided into five subgroups according to the duration of the period of caries induction (4–20 days). The enamel blocks were immersed in cariogenic solution containing the microorganisms, which was changed every 48 h. Groups C and D presented lower surface hardness values (SMH) and higher area of hardness loss (ΔS) after the cariogenic challenge than groups A and B (P < 0.05). As regards lesion depth, under polarized light microscopy, group A presented significantly lower values, and groups C and D the highest values. Group B showed a higher value than group A (P < 0.05). Groups A and B exhibited subsurface caries lesions after all treatment durations, while groups C and D presented erosion‐type lesions with surface softening. The model using S. mutans, whether or not it was associated with L. acidophilus, was less aggressive and may be used for the induction of non‐cavitated enamel caries‐like lesions. The optimal period for inducing caries‐like lesions was 8 days. Microsc. Res. Tech. 78:444–451, 2015. © 2015 Wiley Periodicals, Inc.     

Optimization of ODHE membrane reactor based on mixed ionic electronic conductor using soft computing techniques

This work presents the optimization of the operating conditions of a membrane reactor for the oxidative dehydrogenation of ethane. The catalytic membrane reactor is based on a mixed ionic–electronic conducting material, i.e. Ba_0.5Sr_0.5Co_0.8Fe_0.2O_δ−3, which presents high oxygen flux above 750 °C under sufficient chemical potential gradient. Specifically, diluted ethane is fed into the reactor chamber and air (or diluted air) is flushed to the other side of the membrane. A framework based on Soft Computing techniques has been used to maximize the ethylene yield by simultaneously varying five operation variables: nominal reactor temperature (Temp); gas flow in the reaction compartment (QHC); gas flow in the oxygen-rich compartment (QAir); ethane concentration in the reaction compartment (%C₂H₆); and oxygen concentration in oxygen-rich compartment (%O₂). The optimization tool combines a genetic algorithm guided by a neural network model. This shows how the neural network model for this particular problem is obtained and the analysis of its behavior along the optimization process. The optimization process is analyzed in terms of: (1) catalytic figures of merit, i.e., evolution of yield and selectivity towards different products and (2) framework behavior and variable significance. The two experimental areas maximizing the ethylene yield are explored and analyzed. The highest yield reached in the optimization process exceeded 87%.     

Superconducting Vortex Lattice Configurations on Periodic Potentials: Simulation and Experiment

Nb films have been fabricated on top of array of Ni nanodots. The array of periodic pinning potentials modifies the vortex lattice for specific values of the external applied magnetic field. By means of an implemented code developed from scratch, computer simulations based only on the vortex?Cvortex and the vortex?Cnanodot interactions provide the total interaction between vortices and pinning sites as well as the position of the vortices in the array unit cell. This simulation approach could be performed on square, rectangular or triangular arrays of nanodefects of different size.