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

The economic opportunities and constraints of green growth

노트 : Asie.Visions is an electronic publication dedicated to Asia. With contributions by French and international experts, Asie.Visions deals with economic, strategic, and political issues. The collection aims to contribute to the global debate and to a better understanding of the regional issues at stake. It is published in French and/or in English and upholds Ifri’s standards of quality (editing and anonymous peerreview)

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

Prevalence of metabolic syndrome and related factors in Taiwanese high-tech industry workers

OBJECTIVES: In light of the increasing number of high-tech industry workers and the differences in their working conditions compared to those of the general population, the health status of these workers merits serious attention. This study aimed to explore the prevalence of metabolic syndrome and its correlates among Taiwanese high-tech industry workers. METHODS: This cross-sectional study included 4,666 workers who participated in labor health examinations at a hospital in southern Taiwan in 2008. Participants with metabolic syndrome were defined using the criteria proposed by the Taiwan National Department of Health in 2007. Factors associated with metabolic syndrome were determined using multiple logistic regression analysis. RESULTS: The overall prevalence of metabolic syndrome was 8.2%, and the prevalence was higher in men than in women (14.0% vs. 2.3%,

Production of 2,3-butanediol in Saccharomyces cerevisiae by in silico aided metabolic engineering

BACKGROUND: 2,3-Butanediol is a chemical compound of increasing interest due to its wide applications. It can be synthesized via mixed acid fermentation of pathogenic bacteria such as Enterobacter aerogenes and Klebsiella oxytoca. The non-pathogenic Saccharomyces cerevisiae possesses three different 2,3-butanediol biosynthetic pathways, but produces minute amount of 2,3-butanediol. Hence, we attempted to engineer S. cerevisiae strain to enhance 2,3-butanediol production. RESULTS: We first identified gene deletion strategy by performing in silico genome-scale metabolic analysis. Based on the best in silico strategy, in which disruption of alcohol dehydrogenase (ADH) pathway is required, we then constructed gene deletion mutant strains and performed batch cultivation of the strains. Deletion of three ADH genes, ADH1, ADH3 and ADH5, increased 2,3-butanediol production by 55-fold under microaerobic condition. However, overproduction of glycerol was observed in this triple deletion strain. Additional rational design to reduce glycerol production by GPD2 deletion altered the carbon fluxes back to ethanol and significantly reduced 2,3-butanediol production. Deletion of ALD6 reduced acetate production in strains lacking major ADH isozymes, but it did not favor 2,3-butanediol production. Finally, we introduced 2,3-butanediol biosynthetic pathway from Bacillus subtilis and E. aerogenes to the engineered strain and successfully increased titer and yield. Highest 2,3-butanediol titer (2.29 g·l(-1)) and yield (0.113 g·g(-1)) were achieved by Δadh1 Δadh3 Δadh5 strain under anaerobic condition. CONCLUSIONS: With the aid of in silico metabolic engineering, we have successfully designed and constructed S. cerevisiae strains with improved 2,3-butanediol production

Karyotype and nucleic acid content in Zantedeschia aethiopica Spr. and Zantedeschia elliottiana Engl.

Analysis of karyotype, nucleic deoxyribonucleic acid (DNA) content and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) were performed in Zantedeschia aethiopica and Zantedeschia elliottiana. Mitotic metaphase in both species showed 2n=32. The chromosomes of both species were quite similar with medium length ranging from 1.55 ± 0.04 to 3.85 ± 0.12 μM in Z. aethiopica and 2.15 ± 0.04 to 3.90 ± 0.12 μM in Z. elliottiana. However, some differences were found in morphology and centromeric position among the chromosomes. Identification of individual chromosomes was carried out using chromosomes length, and centromeric positions. The karyotype of Z. aethiopica was determined to be 2n = 32 = 14 m + 18 sm and of Z. elliottiana to be 2n = 32 = 10 m + 22 sm. The 2C nuclear DNA content was found to be 3.72 ± 0.10 picograms (equivalent to 3638.16 mega base pairs) for Z. aethiopica and 1144.26 ± 0.05 picograms (equivalent to 1144.26 mega base pairs) for Z. elliottiana. Leaf protein analysis showed 11 and 9 bands for Z. aethiopica and Z. elliottiana, respectively, among which some were species specific. These results may provide useful information regarding Zantedeschia for the study of taxonomic relationships, genetics and breeding.Keywords: Zantedeschia, karyotype, mitotic metaphase, chromosomes, flow cytometr