DHLP 1&2: Giraph based distributed label propagation algorithms on heterogeneous drug-related networks

Background and Objective: Heterogeneous complex networks are large graphs consisting of different types of nodes and edges. The knowledge extraction from these networks is complicated. Moreover, the scale of these networks is steadily increasing. Thus, scalable methods are required. Methods: In this paper, two distributed label propagation algorithms for heterogeneous networks, namely DHLP-1 and DHLP-2 have been introduced. Biological networks are one type of the heterogeneous complex networks. As a case study, we have measured the efficiency of our proposed DHLP-1 and DHLP-2 algorithms on a biological network consisting of drugs, diseases, and targets. The subject we have studied in this network is drug repositioning but our algorithms can be used as general methods for heterogeneous networks other than the biological network. Results: We compared the proposed algorithms with similar non-distributed versions of them namely MINProp and Heter-LP. The experiments revealed the good performance of the algorithms in terms of running time and accuracy.Comment: Source code available for Apache Giraph on Hadoo

Merger enforcement in two-sided markets

This paper studies mergers in two-sided markets by estimating a structural supply and demand model and performing counterfactual experiments. The analysis is performed on data for a merger wave in U.S. radio that occurred between 1996 and 2006. The paper makes two main contributions. First, I identify the conflicting incentives of merged firms to exercise market power on both sides of the market (listeners and advertisers in the case of radio). Second, I disaggregate the effects of mergers on consumers into changes in product variety and changes in supplied ad quantity. I find that firms have moderate market power over listeners in all markets, extensive market power over advertisers in small markets and no market power over advertisers in large markets. Counterfactuals reveal that extra product variety created by post-merger repositioning increased listeners' welfare by 1.3% and decreased advertisers' welfare by about $160m per-year. However, subsequent changes in supplied ad quantity decreased listener welfare by 0.4$140m (for a total impact of -$300m).

Estimation of cost synergies from mergers without cost data: Application to U.S. radio

This paper develops a new way to estimate cost synergies from mergers without using actual data on cost. The estimator uses a structural model in which companies play a dynamic game with endogenous mergers and product repositioning decisions. Such a formulation has several benefits over the widespread static merger analysis. In particular, it corrects for sample selection of more profitable mergers and captures follow-up mergers and post-merger product repositioning. The framework is applied to estimate cost efficiencies after the deregulation of U.S. radio in 1996. The procedure uses the data on radio station characteristics and numerous acquisitions, without explicit need for cost data. It turns out that between 1996 and 2006 additional ownership concentration generated $2.5b per-year cost savings, which is about 10% of total industry revenue.

Groupwise Multimodal Image Registration using Joint Total Variation

In medical imaging it is common practice to acquire a wide range of modalities (MRI, CT, PET, etc.), to highlight different structures or pathologies. As patient movement between scans or scanning session is unavoidable, registration is often an essential step before any subsequent image analysis. In this paper, we introduce a cost function based on joint total variation for such multimodal image registration. This cost function has the advantage of enabling principled, groupwise alignment of multiple images, whilst being insensitive to strong intensity non-uniformities. We evaluate our algorithm on rigidly aligning both simulated and real 3D brain scans. This validation shows robustness to strong intensity non-uniformities and low registration errors for CT/PET to MRI alignment. Our implementation is publicly available at https://github.com/brudfors/coregistration-njtv

Measurement and effects of teaching quality : an empirical model applied to masters programs

This study applies service quality and customer satisfaction theory to the field of education, and particularly to postgraduate studies. It examines the impact of multiple indicators of teaching quality on student satisfaction. For this purpose, a model is proposed and verified in which the teaching quality indicators are antecedents of the student's satisfaction with the professor and the program. An innovative aspect of the study is the introduction into education of the concept of customer loyalty as a result of satisfaction. In its analysis of these aspects, the study draws on data from a survey conducted among students of two business administration programs. A total of 2,446 valid questionnaires were obtained. In the proposed model, the latent variable, student satisfaction, is considered to be a consequence of the combined effect of satisfaction with certain aspects of teaching quality and the cause of the variation in the indicators on the satisfaction measurement scale. The model was tested by using the MIMIC [Multiple Indicators and Multiple Causes] structural equation technique