Testing the Distance-Duality Relation with a Combination of Cosmological Distance Observations

In this paper, we propose an accurate test of the distance-duality (DD) relation, $\eta=D_{L}(z)(1+z)^{-2}/D_{A}(z)=1$ (where $D_{L}$ and $D_{A}$ are the luminosity distances and angular diameter distances, respectively), with a combination of cosmological observational data of Type Ia Supernave (SNe Ia) from Union2 set and the galaxy cluster sample under an assumption of spherical model. In order to avoid bias brought by redshift incoincidence between observational data and to consider redshift error bars of both clusters and SNe Ia in analysis, we carefully choose the SNe Ia points which have the minimum acceptable redshift difference of the galaxy cluster sample ($|\Delta z|_{\rm min} =\sigma_{z, \rm SN}+\sigma_{z, \rm cluster}$). By assuming $\eta$ a constant and functions of the redshift parameterized by six different expressions, we find that there exists no conceivable evidence for variations in the DD relation concerning with observational data, since it is well satisfied within $1\sigma$ confidence level for most cases. Further considering different values of $\Delta z$ in constraining, we also find that the choosing of $\Delta z$ may play an important role in this model-independent test of the distance-duality relation for the spherical sample of galaxy clusters.Comment: 9 pages, 4 figures, 1 table. accepted for publication in Res. Astron. Astrophy

ヒトの高周波振動知覚の類似特性に基づく触覚変調

Tohoku University昆陽雅司課

Replacing the Irreplaceable: Fast Algorithms for Team Member Recommendation

In this paper, we study the problem of Team Member Replacement: given a team of people embedded in a social network working on the same task, find a good candidate who can fit in the team after one team member becomes unavailable. We conjecture that a good team member replacement should have good skill matching as well as good structure matching. We formulate this problem using the concept of graph kernel. To tackle the computational challenges, we propose a family of fast algorithms by (a) designing effective pruning strategies, and (b) exploring the smoothness between the existing and the new team structures. We conduct extensive experimental evaluations on real world datasets to demonstrate the effectiveness and efficiency. Our algorithms (a) perform significantly better than the alternative choices in terms of both precision and recall; and (b) scale sub-linearly.Comment: Initially submitted to KDD 201

An intervention to improve provider-patient interaction at methadone maintenance treatment in China.

BackgroundThis study evaluated an intervention aiming to improve methadone maintenance therapy (MMT) service providers' interaction with their patients in China.MethodsSixty-eight MMT clinics were randomized to either an intervention or a control condition. Providers in the intervention group attended three group training sessions to enhance their communication skills. Trained providers were encouraged to practice the taught communication skills through provider-initiated individual sessions with their patients. A total of 418 service providers completed assessments from baseline to 24-month. Linear mixed-effects regression models were used to compare self-reported short-term and sustained improvement in provider-patient interaction between the intervention and the control conditions.ResultsThe intervention group service providers perceived significantly greater short-term and sustained improvement in provider-patient interaction compared to the control group service providers (estimated difference (±SE): 1.20 (0.24) and 1.35 (0.33), respectively; p-values < 0.0001). Providers' baseline job satisfaction was significantly associated with a greater perceived improvement in provider-patient interaction for both periods (reg. coef. (±SE): 0.02 (0.01) and 0.04 (0.01) for short-term and sustained periods, respectively; p-values < 0.01).ConclusionStudy findings suggest that the intervention could be beneficial for improving perceived provider-patient interaction in MMT programs. Service providers' job satisfaction should be addressed in training programs for the improvement of provider-patient interaction