Location, Proximity, and M&A Transactions

In this paper, we examine how the geographic location of firms affects acquisition decisions and value creation for acquirers in takeover transactions. We find that firms located in an urban area are more likely to receive a takeover bid and complete a takeover transaction as a target than firms located in rural areas, and takeover deals involving an urban target are associated with higher acquirer announcement returns, after controlling for the proximity between the target and the acquirer. In addition, a target\u27s urban location significantly attenuates the negative effect of a long distance between the target and the acquirer on acquirer returns, a fact that is documented in the existing literature. Our findings reveal a previously underexplored force—firm location—that can affect takeover transactions, in addition to proximity. Our paper suggests that a firm\u27s location plays an important role in facilitating the dissemination of soft information and enhancing information-based synergies

A Class of Second Order Difference Approximation for Solving Space Fractional Diffusion Equations

A class of second order approximations, called the weighted and shifted Gr\"{u}nwald difference operators, are proposed for Riemann-Liouville fractional derivatives, with their effective applications to numerically solving space fractional diffusion equations in one and two dimensions. The stability and convergence of our difference schemes for space fractional diffusion equations with constant coefficients in one and two dimensions are theoretically established. Several numerical examples are implemented to testify the efficiency of the numerical schemes and confirm the convergence order, and the numerical results for variable coefficients problem are also presented.Comment: 24 Page

Pulsars identified from the NRAO VLA Sky Survey

We identified 97 strong pulsars from the NRAO VLA Sky Survey (NVSS) at 1.4 GHz north of Dec(J2000) >-40\degr. The total flux density, linear polarization intensity and polarization angle (PA) of all pulsars are extracted from the NVSS catalog. The well-calibrated PA measurement of 5 pulsars can be used for absolute PA calibrations in other observations. Comparing the source positions with those in the pulsar catalog, we got the first measurement of the proper motion upper limit of PSR B0031-07, which is $\mu_{\alpha}\cos\delta = -102 \pm 74 mas/yr$ and $\mu_{\delta} = -105 \pm 78 mas/yr$.Comment: 7 pages; 3 figures; one big table; To appear in A&A Supplement

Coalitional Game Theoretic Approach for Cooperative Transmission in Vehicular Networks

Cooperative transmission in vehicular networks is studied by using coalitional game and pricing in this paper. There are several vehicles and roadside units (RSUs) in the networks. Each vehicle has a desire to transmit with a certain probability, which represents its data burtiness. The RSUs can enhance the vehicles' transmissions by cooperatively relaying the vehicles' data. We consider two kinds of cooperations: cooperation among the vehicles and cooperation between the vehicle and RSU. First, vehicles cooperate to avoid interfering transmissions by scheduling the transmissions of the vehicles in each coalition. Second, a RSU can join some coalition to cooperate the transmissions of the vehicles in that coalition. Moreover, due to the mobility of the vehicles, we introduce the notion of encounter between the vehicle and RSU to indicate the availability of the relay in space. To stimulate the RSU's cooperative relaying for the vehicles, the pricing mechanism is applied. A non-transferable utility (NTU) game is developed to analyze the behaviors of the vehicles and RSUs. The stability of the formulated game is studied. Finally, we present and discuss the numerical results for the 2-vehicle and 2-RSU scenario, and the numerical results verify the theoretical analysis.Comment: accepted by IEEE ICC'1

A Cross-layer Perspective on Energy Harvesting Aided Green Communications over Fading Channels

We consider the power allocation of the physical layer and the buffer delay of the upper application layer in energy harvesting green networks. The total power required for reliable transmission includes the transmission power and the circuit power. The harvested power (which is stored in a battery) and the grid power constitute the power resource. The uncertainty of data generated from the upper layer, the intermittence of the harvested energy, and the variation of the fading channel are taken into account and described as independent Markov processes. In each transmission, the transmitter decides the transmission rate as well as the allocated power from the battery, and the rest of the required power will be supplied by the power grid. The objective is to find an allocation sequence of transmission rate and battery power to minimize the long-term average buffer delay under the average grid power constraint. A stochastic optimization problem is formulated accordingly to find such transmission rate and battery power sequence. Furthermore, the optimization problem is reformulated as a constrained MDP problem whose policy is a two-dimensional vector with the transmission rate and the power allocation of the battery as its elements. We prove that the optimal policy of the constrained MDP can be obtained by solving the unconstrained MDP. Then we focus on the analysis of the unconstrained average-cost MDP. The structural properties of the average optimal policy are derived. Moreover, we discuss the relations between elements of the two-dimensional policy. Next, based on the theoretical analysis, the algorithm to find the constrained optimal policy is presented for the finite state space scenario. In addition, heuristic policies with low-complexity are given for the general state space. Finally, simulations are performed under these policies to demonstrate the effectiveness

Charging Scheduling of Electric Vehicles with Local Renewable Energy under Uncertain Electric Vehicle Arrival and Grid Power Price

In the paper, we consider delay-optimal charging scheduling of the electric vehicles (EVs) at a charging station with multiple charge points. The charging station is equipped with renewable energy generation devices and can also buy energy from power grid. The uncertainty of the EV arrival, the intermittence of the renewable energy, and the variation of the grid power price are taken into account and described as independent Markov processes. Meanwhile, the charging energy for each EV is random. The goal is to minimize the mean waiting time of EVs under the long term constraint on the cost. We propose queue mapping to convert the EV queue to the charge demand queue and prove the equivalence between the minimization of the two queues' average length. Then we focus on the minimization for the average length of the charge demand queue under long term cost constraint. We propose a framework of Markov decision process (MDP) to investigate this scheduling problem. The system state includes the charge demand queue length, the charge demand arrival, the energy level in the storage battery of the renewable energy, the renewable energy arrival, and the grid power price. Additionally the number of charging demands and the allocated energy from the storage battery compose the two-dimensional policy. We derive two necessary conditions of the optimal policy. Moreover, we discuss the reduction of the two-dimensional policy to be the number of charging demands only. We give the sets of system states for which charging no demand and charging as many demands as possible are optimal, respectively. Finally we investigate the proposed radical policy and conservative policy numerically