Spatio-temporal models are valuable tools for disease mapping and understanding the geographical distribution of diseases and temporal dynamics. Spatio-temporal models have been proven empirically to be very complex a...Spatio-temporal models are valuable tools for disease mapping and understanding the geographical distribution of diseases and temporal dynamics. Spatio-temporal models have been proven empirically to be very complex and this complexity has led many to oversimply and model the spatial and temporal dependencies independently. Unlike common practice, this study formulated a new spatio-temporal model in a Bayesian hierarchical framework that accounts for spatial and temporal dependencies jointly. The spatial and temporal dependencies were dynamically modelled via the matern exponential covariance function. The temporal aspect was captured by the parameters of the exponential with a first-order autoregressive structure. Inferences about the parameters were obtained via Markov Chain Monte Carlo (MCMC) techniques and the spatio-temporal maps were obtained by mapping stable posterior means from the specific location and time from the best model that includes the significant risk factors. The model formulated was fitted to both simulation data and Kenya meningitis incidence data from 2013 to 2019 along with two covariates;Gross County Product (GCP) and average rainfall. The study found that both average rainfall and GCP had a significant positive association with meningitis occurrence. Also, regarding geographical distribution, the spatio-temporal maps showed that meningitis is not evenly distributed across the country as some counties reported a high number of cases compared with other counties.展开更多
<strong>OBJECTIVE</strong><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-...<strong>OBJECTIVE</strong><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><strong>:</strong></span></span></span></span><span><span><span><b><span style="font-family:""> </span></b></span></span></span><span><span><span><span style="font-family:""><span style="font-family:Verdana;">To compare maternal preoperative and postoperative hemoglobin variation after cord clamping. </span><b><span style="font-family:Verdana;">METHODS: </span></b><span style="font-family:Verdana;">Randomized clinical trial performed in Porto Alegre, RS from January to December 2012. It was included 356 women with habitual risk gestations. In the immediate cord clamping group</span></span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span></span><span><span><span><span style="font-family:""><span style="font-family:Verdana;"> the umbilical cord section was realized between 0 and 60 s (group 1) while in the delayed cord clamping group it was realized >60 s (group 2). </span><b><span style="font-family:Verdana;">RESULTS:</span></b><span style="font-family:Verdana;"> The mean (±standard deviation [SD]) preoperative hemoglobin was 12.13 ± 1.06 in the group 1 and 12.13 ± 1.11 in the group 2. The mean (±SD) postoperative day 2 hemoglobin level was 10.19 ± 1.46 in the group 1 and 10.24 ± 1.42 in the group 2. </span><b><span style="font-family:Verdana;">CONCLUSIONS: </span></b><span style="font-family:Verdana;">Delayed umbilical cord clamping resulted in a similar maternal hemoglobin level reduction at postoperative day 2.</span></span></span></span></span>展开更多
Background:Large area forest inventories often use regular grids(with a single random start)of sample locations to ensure a uniform sampling intensity across the space of the surveyed populations.A design-unbiased est...Background:Large area forest inventories often use regular grids(with a single random start)of sample locations to ensure a uniform sampling intensity across the space of the surveyed populations.A design-unbiased estimator of variance does not exist for this design.Oftentimes,a quasi-default estimator applicable to simple random sampling(SRS)is used,even if it carries with it the likely risk of overestimating the variance by a practically important margin.To better exploit the precision of systematic sampling we assess the performance of five estimators of variance,including the quasi default.In this study,simulated systematic sampling was applied to artificial populations with contrasting covariance structures and with or without linear trends.We compared the results obtained with the SRS,Matern’s,successive difference replication,Ripley’s,and D’Orazio’s variance estimators.Results:The variances obtained with the four alternatives to the SRS estimator of variance were strongly correlated,and in all study settings consistently closer to the target design variance than the estimator for SRS.The latter always produced the greatest overestimation.In populations with a near zero spatial autocorrelation,all estimators,performed equally,and delivered estimates close to the actual design variance.Conclusion:Without a linear trend,the SDR and DOR estimators were best with variance estimates more narrowly distributed around the benchmark;yet in terms of the least average absolute deviation,Matern’s estimator held a narrow lead.With a strong or moderate linear trend,Matern’s estimator is choice.In large populations,and a low sampling intensity,the performance of the investigated estimators becomes more similar.展开更多
采用随机几何理论分析异构蜂窝网络性能时,通常假设用户均匀分布且独立于基站。但在实际的异构蜂窝网络中,小基站一般部署在热点地区或覆盖盲区,因此,小基站与用户的空间位置存在相关性。针对三维空间中蜂窝用户以小基站为父节点的Mater...采用随机几何理论分析异构蜂窝网络性能时,通常假设用户均匀分布且独立于基站。但在实际的异构蜂窝网络中,小基站一般部署在热点地区或覆盖盲区,因此,小基站与用户的空间位置存在相关性。针对三维空间中蜂窝用户以小基站为父节点的Matern簇过程和Thomas簇过程进行建模,再采用最大信号干扰比(signal to interference ratio,SIR)的小区接入准则,在瑞利衰落信道下推导出下行链路的覆盖概率;通过蒙特卡罗仿真验证理论结果,分析用户簇过程的半径或方差、SIR门限值、小基站密度和小基站功率对覆盖概率的影响,并比较三维用户簇分布模型、三维用户均匀分布模型和二维用户簇分布模型的网络性能。实验结果表明基于三维用户簇分布模型的异构蜂窝网络具有较好的覆盖概率。展开更多
文摘Spatio-temporal models are valuable tools for disease mapping and understanding the geographical distribution of diseases and temporal dynamics. Spatio-temporal models have been proven empirically to be very complex and this complexity has led many to oversimply and model the spatial and temporal dependencies independently. Unlike common practice, this study formulated a new spatio-temporal model in a Bayesian hierarchical framework that accounts for spatial and temporal dependencies jointly. The spatial and temporal dependencies were dynamically modelled via the matern exponential covariance function. The temporal aspect was captured by the parameters of the exponential with a first-order autoregressive structure. Inferences about the parameters were obtained via Markov Chain Monte Carlo (MCMC) techniques and the spatio-temporal maps were obtained by mapping stable posterior means from the specific location and time from the best model that includes the significant risk factors. The model formulated was fitted to both simulation data and Kenya meningitis incidence data from 2013 to 2019 along with two covariates;Gross County Product (GCP) and average rainfall. The study found that both average rainfall and GCP had a significant positive association with meningitis occurrence. Also, regarding geographical distribution, the spatio-temporal maps showed that meningitis is not evenly distributed across the country as some counties reported a high number of cases compared with other counties.
文摘<strong>OBJECTIVE</strong><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><strong>:</strong></span></span></span></span><span><span><span><b><span style="font-family:""> </span></b></span></span></span><span><span><span><span style="font-family:""><span style="font-family:Verdana;">To compare maternal preoperative and postoperative hemoglobin variation after cord clamping. </span><b><span style="font-family:Verdana;">METHODS: </span></b><span style="font-family:Verdana;">Randomized clinical trial performed in Porto Alegre, RS from January to December 2012. It was included 356 women with habitual risk gestations. In the immediate cord clamping group</span></span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span></span><span><span><span><span style="font-family:""><span style="font-family:Verdana;"> the umbilical cord section was realized between 0 and 60 s (group 1) while in the delayed cord clamping group it was realized >60 s (group 2). </span><b><span style="font-family:Verdana;">RESULTS:</span></b><span style="font-family:Verdana;"> The mean (±standard deviation [SD]) preoperative hemoglobin was 12.13 ± 1.06 in the group 1 and 12.13 ± 1.11 in the group 2. The mean (±SD) postoperative day 2 hemoglobin level was 10.19 ± 1.46 in the group 1 and 10.24 ± 1.42 in the group 2. </span><b><span style="font-family:Verdana;">CONCLUSIONS: </span></b><span style="font-family:Verdana;">Delayed umbilical cord clamping resulted in a similar maternal hemoglobin level reduction at postoperative day 2.</span></span></span></span></span>
文摘Background:Large area forest inventories often use regular grids(with a single random start)of sample locations to ensure a uniform sampling intensity across the space of the surveyed populations.A design-unbiased estimator of variance does not exist for this design.Oftentimes,a quasi-default estimator applicable to simple random sampling(SRS)is used,even if it carries with it the likely risk of overestimating the variance by a practically important margin.To better exploit the precision of systematic sampling we assess the performance of five estimators of variance,including the quasi default.In this study,simulated systematic sampling was applied to artificial populations with contrasting covariance structures and with or without linear trends.We compared the results obtained with the SRS,Matern’s,successive difference replication,Ripley’s,and D’Orazio’s variance estimators.Results:The variances obtained with the four alternatives to the SRS estimator of variance were strongly correlated,and in all study settings consistently closer to the target design variance than the estimator for SRS.The latter always produced the greatest overestimation.In populations with a near zero spatial autocorrelation,all estimators,performed equally,and delivered estimates close to the actual design variance.Conclusion:Without a linear trend,the SDR and DOR estimators were best with variance estimates more narrowly distributed around the benchmark;yet in terms of the least average absolute deviation,Matern’s estimator held a narrow lead.With a strong or moderate linear trend,Matern’s estimator is choice.In large populations,and a low sampling intensity,the performance of the investigated estimators becomes more similar.
文摘采用随机几何理论分析异构蜂窝网络性能时,通常假设用户均匀分布且独立于基站。但在实际的异构蜂窝网络中,小基站一般部署在热点地区或覆盖盲区,因此,小基站与用户的空间位置存在相关性。针对三维空间中蜂窝用户以小基站为父节点的Matern簇过程和Thomas簇过程进行建模,再采用最大信号干扰比(signal to interference ratio,SIR)的小区接入准则,在瑞利衰落信道下推导出下行链路的覆盖概率;通过蒙特卡罗仿真验证理论结果,分析用户簇过程的半径或方差、SIR门限值、小基站密度和小基站功率对覆盖概率的影响,并比较三维用户簇分布模型、三维用户均匀分布模型和二维用户簇分布模型的网络性能。实验结果表明基于三维用户簇分布模型的异构蜂窝网络具有较好的覆盖概率。
