Identifying opportunities for improving the organ supply through race-stratified data

Organ procurement in the US has received attention from government officials and policymakers the last two years, culminating in CMS releasing an updated Final Rule related to organ donation this year. This regulatory change revises how organ procurement organizations (OPOs), the federal contractors tasked with managing deceased donation, are evaluated and certified/de-certified. We used 2019 data and the CMS methodology to calculate race-stratified donation data among racial/ethnic minorities across the 57 OPOs. We found that the variability in donation rates across the 57 OPOs are greater among minority populations than non-Hispanic white potential donors. Among Tier 3 OPOs, there are: a) some with low donation rates across all racial/ethnic groups; b) some with low donation rates among only certain groups, and c) some where donation rates are lowest among non-Hispanic white patients. Among low-performing OPOs, these race/ethnicity-stratified data show that under-performance in certain areas is not due to the population demographics, and identifies areas for targeted interventions to increase donation and avoid decertification

Antique Samarkand or Afrasiab II and III

The article deals with the Antique period of the old Samarkand. Using the old data from the Soviet excavations and the new one coming from the French-Uzbek ones, it gives stratified data leading to a finer distinction of the pottery between periods IIA, IIB and III. Proposals for their absolute dating and interpretation are added.

A Case Similarity Calculation Model Based on the Urban Flooding Case with Stratified Data Characteristics

As the pace of urbanization is accelerating, increasing amount of floodplain has been projected as the future cities. Subsequently, urban flooding is being studied by global emergency management exports due to its increasingly significant impact on us. Some existing research on flooding emergency management based on the case-based reasoning (CBR) method have made tremendous progress, but the urban flooding case with its stratified data characteristics is required a new methodology which is different from the ones applied to flash floods. So, based on the case-based reasoning (CBR) method, this paper proposed a CPIE-CBR model with four layers, classification filtration, punctiform similarity, interval similarity and entropy weight method, to calculate the case similarity among the urban flooding case with stratified data characteristics. Then we carry out the numerical simulation with the real data about China and conduct some comparison with original ways so that we observe the validity and efficiency of our model in the end.