Dual-Career Couples in Academia : Does Wage Growth Suffer When One’s Partner Works for the Same University?

Extending the literature on monopsony in academic labor markets, we find that faculty pay is inversely related to seniority in both cross-sectional and longitudinal data sets for a large public university in the United States. Fixed-effects results indicate that the negative relationship cannot be explained by lower quality of senior faculty. Arguing that mobility costs are higher when both partners work for the same university, we allow monopsony power to vary by employment status of partner. We find that pay of male faculty is negatively and significantly related to the number of years the partner has been employed by the university and that the penalty is greater when couples are hired together.Monopsony, academic labor market

Quantile Regression Under Random Censoring

No abstract.

Acanthamoeba genotype T4 from the UK and Iran and isolation of the T2 genotype from clinical isolates

The majority of the keratitis-causing Acanthamoeba isolates are genotype T4. In an attempt to determine whether predominance of T4 isolates in Acanthamoeba keratitis is due to greater virulence or greater prevalence of this genotype, Acanthamoeba genotypes were determined for 13 keratitis isolates and 12 environmental isolates from Iran. Among 13 clinical isolates, eight (61.5 %) belonged to T4, two (15.3 %) belonged to T3 and three (23 %) belonged to the T2 genotype. In contrast, the majority of 12 environmental isolates tested in the present study belonged to T2 (7/12, 58.3 %), followed by 4/12 T4 isolates (33.3 %). In addition, the genotypes of six new Acanthamoeba isolates from UK keratitis cases were determined. Of these, five (83.3 %) belonged to T4 and one was T3 (16.6 %), supporting the expected high frequency of T4 in Acanthamoeba keratitis. In total, the genotypes of 24 Acanthamoeba keratitis isolates from the UK and Iran were determined. Of these, 17 belonged to T4 (70.8 %), three belonged to T2 (12.5 %), three belonged to T3 (12.5 %) and one belonged to T11 (4.1 %), confirming that T4 is the predominant genotype (S2 = 4.167; P = 0.0412) in Acanthamoeba keratitis

A Case for Peering of Content Delivery Networks

The proliferation of Content Delivery Networks (CDN) reveals that existing content networks are owned and operated by individual companies. As a consequence, closed delivery networks are evolved which do not cooperate with other CDNs and in practice, islands of CDNs are formed. Moreover, the logical separation between contents and services in this context results in two content networking domains. But present trends in content networks and content networking capabilities give rise to the interest in interconnecting content networks. Finding ways for distinct content networks to coordinate and cooperate with other content networks is necessary for better overall service. In addition to that, meeting the QoS requirements of users according to the negotiated Service Level Agreements between the user and the content network is a burning issue in this perspective. In this article, we present an open, scalable and Service-Oriented Architecture based system to assist the creation of open Content and Service Delivery Networks (CSDN) that scale and support sharing of resources with other CSDNs.Comment: Short Article (Submitted in DS Online as Work in Progress

Island Loss for Learning Discriminative Features in Facial Expression Recognition

Over the past few years, Convolutional Neural Networks (CNNs) have shown promise on facial expression recognition. However, the performance degrades dramatically under real-world settings due to variations introduced by subtle facial appearance changes, head pose variations, illumination changes, and occlusions. In this paper, a novel island loss is proposed to enhance the discriminative power of the deeply learned features. Specifically, the IL is designed to reduce the intra-class variations while enlarging the inter-class differences simultaneously. Experimental results on four benchmark expression databases have demonstrated that the CNN with the proposed island loss (IL-CNN) outperforms the baseline CNN models with either traditional softmax loss or the center loss and achieves comparable or better performance compared with the state-of-the-art methods for facial expression recognition.Comment: 8 pages, 3 figure