Asymmetric-valued Spectrum Auction and Competition in Wireless Broadband Services

We study bidding and pricing competition between two spiteful mobile network operators (MNOs) with considering their existing spectrum holdings. Given asymmetric-valued spectrum blocks are auctioned off to them via a first-price sealed-bid auction, we investigate the interactions between two spiteful MNOs and users as a three-stage dynamic game and characterize the dynamic game's equilibria. We show an asymmetric pricing structure and different market share between two spiteful MNOs. Perhaps counter-intuitively, our results show that the MNO who acquires the less-valued spectrum block always lowers his service price despite providing double-speed LTE service to users. We also show that the MNO who acquires the high-valued spectrum block, despite charing a higher price, still achieves more market share than the other MNO. We further show that the competition between two MNOs leads to some loss of their revenues. By investigating a cross-over point at which the MNOs' profits are switched, it serves as the benchmark of practical auction designs

Click-aware purchase prediction with push at the top

Eliciting user preferences from purchase records for performing purchase prediction is challenging because negative feedback is not explicitly observed, and because treating all non-purchased items equally as negative feedback is unrealistic. Therefore, in this study, we present a framework that leverages the past click records of users to compensate for the missing user-item interactions of purchase records, i.e., non-purchased items. We begin by formulating various model assumptions, each one assuming a different order of user preferences among purchased, clicked-but-not-purchased, and non-clicked items, to study the usefulness of leveraging click records. We implement the model assumptions using the Bayesian personalized ranking model, which maximizes the area under the curve for bipartite ranking. However, we argue that using click records for bipartite ranking needs a meticulously designed model because of the relative unreliableness of click records compared with that of purchase records. Therefore, we ultimately propose a novel learning-to-rank method, called P3Stop, for performing purchase prediction. The proposed model is customized to be robust to relatively unreliable click records by particularly focusing on the accuracy of top-ranked items. Experimental results on two real-world e-commerce datasets demonstrate that P3STop considerably outperforms the state-of-the-art implicit-feedback-based recommendation methods, especially for top-ranked items.Comment: For the final published journal version, see https://doi.org/10.1016/j.ins.2020.02.06

Sodium Biphenyl as Anolyte for Sodium-Seawater Batteries

Sodium-based battery systems have recently attracted increasing research interest due to the abundant resources employed. Among various material candidates for the negative electrode, sodium metal provides the highest capacity of theoretically 1165 mAh g(-1) and a very low redox potential of -2.71 versus the standard hydrogen electrode. However, the high reactivity of sodium metal toward the commonly used electrolytes results in severe side reactions, including the evolution of gaseous decomposition products, and, in addition, the risk of dendritic sodium growth, potentially causing a disastrous short circuit of the cell. Herein, the use of sodium biphenyl (Na-BP) as anolyte for the Na-seawater batteries (Na-SWB) is investigated. The catholyte for the open-structured positive electrode is natural seawater with sodium cations dissolved therein. Remarkably, the significant electronic and ionic conductivities of the Na-BP anolyte enable a low overpotential for the sodium deposition upon charge, allowing for high capacity and excellent capacity retention for 80 cycles in full Na-SWB. Additionally, the Na-BP anolyte suppresses gas evolution and dendrite growth by forming a homogeneous surface layer on the metallic negative electrode

Singlet Fermionic Dark Matter with Dark ZZ

We present a fermionic dark matter model mediated by the hidden gauge boson. We assume the QED-like hidden sector which consists of a Dirac fermion and U(1)$_X$ gauge symmetry, and introduce an additional scalar electroweak doublet field with the U(1)$_X$ charge as a mediator. The hidden U(1)$_X$ symmetry is spontaneously broken by the electroweak symmetry breaking and there exists a massive extra neutral gauge boson in this model which is the mediator between the hidden and visible sectors. Due to the U(1)$_X$ charge, the additional scalar doublet does not couple to the Standard Model fermions, which leads to the Higgs sector of type I two Higgs doublet model. The new gauge boson couples to the Standard Model fermions with couplings proportional to those of the ordinary $Z$ boson but very suppressed, thus we call it the dark $Z$ boson. We study the phenomenology of the dark $Z$ boson and the Higgs sector, and show the hidden fermion can be the dark matter candidate.Comment: 10 pages, 3 figure