Mathematical geology最新文献

Current insights into the role of PKA phosphorylation in CFTR channel activity and the pharmacological rescue of cystic fibrosis disease-causing mutants. 目前对 PKA 磷酸化在 CFTR 通道活性中的作用以及对囊性纤维化致病突变体的药理拯救的见解。

IF 8

Mathematical geology Pub Date : 2017-01-01 Epub Date: 2016-10-08 DOI: 10.1007/s00018-016-2388-6

Stephanie Chin, Maurita Hung, Christine E Bear

引用次数: 0

Medical Geography: a Promising Field of Application for Geostatistics. 医学地理学:地统计学的一个有前途的应用领域。

Mathematical geology Pub Date : 2009-01-01 DOI: 10.1007/s11004-008-9211-3

P Goovaerts

{"title":"Medical Geography: a Promising Field of Application for Geostatistics.","authors":"P Goovaerts","doi":"10.1007/s11004-008-9211-3","DOIUrl":"https://doi.org/10.1007/s11004-008-9211-3","url":null,"abstract":"The analysis of health data and putative covariates, such as environmental, socio-economic, behavioral or demographic factors, is a promising application for geostatistics. It presents, however, several methodological challenges that arise from the fact that data are typically aggregated over irregular spatial supports and consist of a numerator and a denominator (i.e. population size). This paper presents an overview of recent developments in the field of health geostatistics, with an emphasis on three main steps in the analysis of areal health data: estimation of the underlying disease risk, detection of areas with significantly higher risk, and analysis of relationships with putative risk factors. The analysis is illustrated using age-adjusted cervix cancer mortality rates recorded over the 1970-1994 period for 118 counties of four states in the Western USA. Poisson kriging allows the filtering of noisy mortality rates computed from small population sizes, enhancing the correlation with two putative explanatory variables: percentage of habitants living below the federally defined poverty line, and percentage of Hispanic females. Area-to-point kriging formulation creates continuous maps of mortality risk, reducing the visual bias associated with the interpretation of choropleth maps. Stochastic simulation is used to generate realizations of cancer mortality maps, which allows one to quantify numerically how the uncertainty about the spatial distribution of health outcomes translates into uncertainty about the location of clusters of high values or the correlation with covariates. Last, geographically-weighted regression highlights the non-stationarity in the explanatory power of covariates: the higher mortality values along the coast are better explained by the two covariates than the lower risk recorded in Utah.","PeriodicalId":88039,"journal":{"name":"Mathematical geology","volume":"41 ","pages":"243-264"},"PeriodicalIF":0.0,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s11004-008-9211-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"28149698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 60

Kriging and Semivariogram Deconvolution in the Presence of Irregular Geographical Units. 不规则地理单元存在下的Kriging和半变差反卷积。

Mathematical geology Pub Date : 2008-01-01

Pierre Goovaerts

{"title":"Kriging and Semivariogram Deconvolution in the Presence of Irregular Geographical Units.","authors":"Pierre Goovaerts","doi":"","DOIUrl":"","url":null,"abstract":"This paper presents a methodology to conduct geostatistical variography and interpolation on areal data measured over geographical units (or blocks) with different sizes and shapes, while accounting for heterogeneous weight or kernel functions within those units. The deconvolution method is iterative and seeks the pointsupport model that minimizes the difference between the theoretically regularized semivariogram model and the model fitted to areal data. This model is then used in area-to-point (ATP) kriging to map the spatial distribution of the attribute of interest within each geographical unit. The coherence constraint ensures that the weighted average of kriged estimates equals the areal datum.This approach is illustrated using health data (cancer rates aggregated at the county level) and population density surface as a kernel function. Simulations are conducted over two regions with contrasting county geographies: the state of Indiana and four states in the Western United States. In both regions, the deconvolution approach yields a point support semivariogram model that is reasonably close to the semivariogram of simulated point values. The use of this model in ATP kriging yields a more accurate prediction than a naïve point kriging of areal data that simply collapses each county into its geographic centroid. ATP kriging reduces the smoothing effect and is robust with respect to small differences in the point support semivariogram model. Important features of the point-support semivariogram, such as the nugget effect, can never be fully validated from areal data. The user may want to narrow down the set of solutions based on his knowledge of the phenomenon (e.g., set the nugget effect to zero). The approach presented avoids the visual bias associated with the interpretation of choropleth maps and should facilitate the analysis of relationships between variables measured over different spatial supports.","PeriodicalId":88039,"journal":{"name":"Mathematical geology","volume":"40 1","pages":"101-128"},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2518693/pdf/nihms-36655.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"27615577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Nu Expression for Probabilistic Data Integration 概率数据集成的Nu表达式

Mathematical geology Pub Date : 2007-10-12 DOI: 10.1007/S11004-007-9117-5

E. I. Polyakova, A. Journel

引用次数: 37

The Discrete Cosine Transform, a Fourier-related Method for Morphometric Analysis of Open Contours 离散余弦变换，开放轮廓形态计量分析的傅里叶相关方法

Mathematical geology Pub Date : 2007-10-05 DOI: 10.1007/S11004-007-9124-6

C. H. Dommergues, J. Dommergues, É. Verrecchia

引用次数: 28

Two Supervised Neural Networks for Classification of Sedimentary Organic Matter Images from Palynological Preparations 两种监督神经网络用于孢粉制备的沉积有机质图像分类

Mathematical geology Pub Date : 2007-10-05 DOI: 10.1007/S11004-007-9120-X

Andrew F. Weller, A. Harris, J. Ware