Purpose:It remains unclear whether preoperative central graft thickness (CGT) contributes to visual outcomes of Descemet stripping automated endothelial keratoplasty (DSAEK). This retrospective cohort study examined the ability of preoperative and postoperative CGT to predict 12-month best spectacle-corrected visual acuity (BSCVA) after DSAEK for Fuchs endothelial corneal dystrophy/moderate pseudophakic bullous keratopathy/second graft.Methods:All consecutive patients who underwent DSAEK in 2015 to 2018 were included. The primary end point was 12-month BSCVA. DSAEK-CGT was measured preoperatively and 6 times between postoperative day 8 and month 12. Eyes were divided according to preoperative CGT 130 m (ultrathin-DSAEK threshold) or 6-month postoperative CGT 100 m (mean 6-month postoperative DSAEK-CGT). The t test assessed CGT evolution of the 4 groups over time. Multivariate analyses examined whether preoperative CGT or 6-month CGT categories predicted 12-month BSCVA. Multivariate analysis assessed the preoperative/perioperative factors that predicted 6-month CGT.Results:A total of 108 eyes (68 patients) underwent DSAEK. Preoperative CGT was >130 and ≤130 m in 87 and 21 eyes, respectively. Postoperative CGT was >100 and ≤100 m in 50 and 58 eyes, respectively. Thin 6-month postoperative grafts thinned significantly more relative to preoperative thickness than thick grafts (P < 0.001). Preoperative CGT subgroups did not show this difference. Six-month postoperative CGT (P = 0.01), but not preoperative CGT, predicted 12-month BSCVA. Preoperative CGT strongly predicted 6-month CGT (P = 0.0003).Conclusions:Postoperative, but not preoperative, DSAEK-CGT predicted 6-month BSCVA. The correlation between preoperative and postoperative CGT and interstudy variation in preoperative CGT measurement accuracy may explain literature disparities regarding the importance of preoperative CGT in DSAEK outcomes.@en

In recent years, implementing a circular economy in cities has been considered by policy makers as a potential solution for achieving sustainability. Existing literature on circular cities is mainly focused on two perspectives: urban governance and urban metabolism. Both these perspectives, to some extent, miss an understanding of space. A spatial perspective is important because circular activities, such as the recycling, reuse, or storage of materials, require space and have a location. It is therefore useful to understand where circular activities are located, and how they are affected by their location and surrounding geography. This study therefore aims to understand the existing state of waste reuse activities in the Netherlands from a spatial perspective, by analyzing the degree, scale, and locations of spatial clusters of waste reuse. This was done by measuring the spatial autocorrelation of waste reuse locations using global and local Moran’s I, with waste reuse data from the national waste registry of the Netherlands. The analysis was done for 10 material types: minerals, plastic, wood and paper, fertilizer, food, machinery and electronics, metal, mixed construction materials, glass, and textile. It was found that all materials except for glass and textiles formed spatial clusters. By varying the grid cell sizes used for data aggregation, it was found that different materials had different “best fit” cell sizes where spatial clustering was the strongest. The best fit cell size is ∼7 km for materials associated with construction and agricultural industries, and ∼20–25 km for plastic and metals.The best fit cell sizes indicate the average distance of companies from each other within clusters, and suggest a suitable spatial resolution at which the material can be understood. Hotspot maps were also produced for each material to show where reuse activities are most spatially concentrated.@en

Background: Solid evidence of the safety and effectiveness of retinoblastoma (RB) conservative treatment using thermotherapy and systemic chemotherapy with long-term follow-up is scarce, especially in low-resource countries. Aims: This study examined the outcomes of this treatment and associated predictors in Vietnam to strengthen the current RB treatment protocol focusing on preserving eye and vision in low-resource settings. Methods and results: A prospective cohort study was conducted at Ho Chi Minh City Eye Hospital in Vietnam from 2005 to 2019. All eligible patients with bilateral RB (one eye already removed and another eye classified as group A or B) and without previous treatment were recruited. All patients received thermotherapy and six cycles of systemic three-agent chemotherapy repeated every 4 weeks. A standardized questionnaire was used to collect information on study participants' age, symptoms, tumor characteristics, treatment, and outcomes. Among 50 eyes of all 50 patients with a median age of 9 (4–20) months, 34 eyes were in group B (68%). The median follow-up time was 60 (60–84) months. All 139 preserved tumors regressed mostly to type 4 (70.4%) and type 3 (23.7%) scars. Kaplan–Meier analysis found the overall globe-salvage rate at 5 years of 91.9% (95% CI: 80.1%–97.7%). Most eyes (41/50, 82%, 95% CI: 69.2%–90.2%) had a final visual acuity ≥0.1. The visual acuity is higher when tumors regressed to a type 4 scar (p =.007, AOR = 8.098, 95% CI: 1.79–36.53) which also shows less enucleation than a type 3 scar (p =.002, AOR = 0.06, 95% CI: 0.01–0.37%). Gender effect on visual acuity after treatment was significant and may be due to discrimination. No major complications were recorded. Conclusion: Conservative treatment of early-stage RB is safe and effective. Long-term, thorough follow-ups of patients post-treatment are needed. The regression patterns of scars could be a useful indicator of treatment failure.@en

We study nonparametric estimators of conditional Kendall's tau, a measure of concordance between two random variables given some covariates. We prove non-asymptotic pointwise and uniform bounds, that hold with high probabilities. We provide "direct proofs" of the consistency and the asymptotic law of conditional Kendall's tau. A simulation study evaluates the numerical performance of such nonparametric estimators. An application to the dependence between energy consumption and temperature conditionally to calendar days is finally provided.@en

Collection of accurate and representative data from agricultural fields is required for efficient crop management. Since growers have limited available resources, there is a need for advanced methods to select representative points within a field in order to best satisfy sampling or sensing objectives. The main purpose of this work was to develop a data-driven method for selecting locations across an agricultural field given observations of some covariates at every point in the field. These chosen locations should be representative of the distribution of the covariates in the entire population and represent the spatial variability in the field. They can then be used to sample an unknown target feature whose sampling is expensive and cannot be realistically done at the population scale. An algorithm for determining these optimal sampling locations, namely the multifunctional matching (MFM) criterion, was based on matching of moments (functionals) between sample and population. The selected functionals in this study were standard deviation, mean, and Kendall's tau. An additional algorithm defined the minimal number of observations that could represent the population according to a desired level of accuracy. The MFM was applied to datasets from two agricultural plots: a vineyard and a peach orchard. The data from the plots included measured values of slope, topographic wetness index, normalized difference vegetation index, and apparent soil electrical conductivity. The MFM algorithm selected the number of sampling points according to a representation accuracy of 90% and determined the optimal location of these points. The algorithm was validated against values of vine or tree water status measured as crop water stress index (CWSI). Algorithm performance was then compared to two other sampling methods: the conditioned Latin hypercube sampling (cLHS) model and a uniform random sample with spatial constraints. Comparison among sampling methods was based on measures of similarity between the target variable population distribution and the distribution of the selected sample. MFM represented CWSI distribution better than the cLHS and the uniform random sampling, and the selected locations showed smaller deviations from the mean and standard deviation of the entire population. The MFM functioned better in the vineyard, where spatial variability was larger than in the orchard. In both plots, the spatial pattern of the selected samples captured the spatial variability of CWSI. MFM can be adjusted and applied using other moments/functionals and may be adopted by other disciplines, particularly in cases where small sample sizes are desired.@en

Several procedures have been recently proposed to test the simplifying assumption for conditional copulas. Instead of considering pointwise conditioning events, we study the constancy of the conditional dependence structure when some covariates belong to general Borel conditioning subsets. We introduce several test statistics based on the equality of conditional Kendall's taus and derive their asymptotic distributions under the null hypothesis. In settings where such conditioning events are not fixed ex ante, we propose a data-driven procedure to recursively build such relevant subsets. This procedure is based on decision trees that maximize the differences between the conditional Kendall's taus, which correspond to the leaves of the trees. Empirical results for such tests are illustrated in the Supplementary Material. Moreover, a study of the conditional dependence between financial stock returns is presented and highlights specific contagion effects of past returns. The last application deals with conditional dependence between coverage amounts in an insurance dataset.@en