Abstract Background Information addressing soil quality in developing countries often depends on results from small experimental plots, which are later extrapolated to vast areas of agricultural land. This approach misinformation end-users land for sustainable nutrient management. The objective this study was estimate the spatial variability index (SQI) at regional scale with predictive models ...

Identifying replicable genetic variants for addiction has been extremely challenging. Besides the common difficulties with genome-wide association studies (GWAS), environmental factors are known to be critical to addiction, and comorbidity is widely observed. Despite the importance of environmental factors and comorbidity for addiction study, few GWAS analyses adequately considered them due to ...

In this study we evaluated residential location as a potential determinant for exposure to organochlorine compounds. We investigated the geographic distribution characteristics of organochlorine levels in approximately 1,374 blood samples collected in 1974 from residents of a community with a potential organochlorine source. Street addresses of Washington County, Maryland, residents were obtain...

The associations were quantified between daily and interannual variation in the timing of a closed population of lake sturgeon Acipenser fulvescens migration and arrival at spawning sites with stream environmental and lunar covariates. Spawning data were gathered from 1262 fish in Black Lake, Michigan 2001 to 2008 and by video monitoring 2000 to 2002. Sex-specific variation in responses to exte...

There are few studies of environmental factors in familial forms of schizophrenia. We investigated whether childhood adversity or environmental factors were associated with schizophrenia in a familial sample where schizophrenia is associated with the NOSA1P gene. We found that a cumulative adversity index including childhood illness, family instability and cannabis use was significantly associa...

The often-used ACE model which decomposes phenotypic variance into additive genetic (A), common-environmental (C) and unique-environmental (E) parts can be extended to include covariates. Collection of these variables however often leads to a large amount of missing data, for example when self-reports (e.g. questionnaires) are not fully completed. The usual approach to handle missing covariate ...

Analysis of spatial and temporal patterns of diversity and abundance in ecological data has been an important focus in ecology. Nevertheless, ecological data such as multi-species data sets are often difficult to analyze because species are usually unevenly represented and multiple environmental covariates may describe their distributions. Although typical univariate, bivariate, and multivariat...

The health implications of environmental noise, especially cardiovascular effects, have been studied intensively. Research on associations between noise and mental health, however, has shown contradictory results. The present study examined associations between individual levels of noise annoyance due to noise from various sources in the living environment and mental health of adults in Germany...

Machine learning and geostatistics are efficient techniques for investigating the geographic distribution of soil properties. This study’s objectives were to assess fertility status, map spatial variability selected parameters compare random forest with ordinary kriging. Soil samples collected analyze parameters: pH, cation exchange capacity (CEC) organic carbon (OC) using systematic sampling. ...

With the development of next generation sequencing technology, researchers have now been able to study the microbiome composition using direct sequencing, whose output are bacterial taxa counts for each microbiome sample. One goal of microbiome study is to associate the microbiome composition with environmental covariates. We propose to model the taxa counts using a Dirichlet-multinomial (DM) r...