22 papers · ranked by Valyu relevance
Panahbehagh, Bardia, Mohebbi, Mehdi + 2 more
Well-spread samples are desirable in many disciplines because they improve estimation when target variables exhibit spatial structure. This paper introduces an integrated methodological framework for spreading samples over the population's spatial coordinates. First, we propose a new, translation-invariant spreadness…
Meirong Chen, Olesya Dulya, Vladimir Mikryukov, Ovidiu Copot + 2 more
Biodiversity surveys require an appropriate sampling design for optimal performance and comparability across space and time and across studies. Based on PacBio and Illumina amplicon sequencing of animals, bacteria and fungi, we assessed and compared various soil sampling designs from widely used continental and global…
Maria Kostakou, Niklas Neisse, Kezia Goldmann, Antonis Chatzinotas + 1 more
Soil microbial diversity is shaped by the spatial scale at which communities are sampled, yet standard sampling practices often homogenize samples, obscuring fine-scale spatial structure and diversity patterns. To better understand how sampling effort, spatial extent, and physical homogenization influence plot-level…
Shuqi Lin, Joshua L. Warren
Although spatial models for areal data are widely used in multilevel settings, the conditions under which spatial and nonspatial random effects yield equivalent posterior inference for regression coefficients have never been formally characterized. We address this question within a hierarchical Bayesian framework for…
Lee Joo-Yeon, S. M., Kwiatkowski, Evan + 1 more
Cluster randomized trials (CRTs) offer a practical alternative for addressing logistical challenges and ensuring feasibility in community health, education, and prevention studies, even though randomized controlled trials are considered the gold standard in evaluating therapeutic interventions. Despite their utility…
Debjoy Thakur, Lingyuan Zhao, Soutir Bandyopadhyay
A major public health concern in the United States (US) is gunrelated deaths. The number of gun injuries largely varies spatially because of county-wise heterogeneity of race, sex, age, and income distributions. But still, a major challenge is to locally identify the influential socio-economic factors behind these…
Jinpu Li, Mauminah Raina, Yiqing Wang, Shuai Zeng + 20 more
Emerging spatial multi-omics technologies enable the profiling of molecular variation within its tissue context, yet existing methods for identifying spatially variable features lack principled approaches to experimental design and cross-sample inference. Here, we present STORM, a principled Statistical TOol for…
Andreia Monteiro, Isabel Natário, Ivone Figueiredo, Paula Simões
In geostatistics, it is commonly assumed that sampling locations are selected independently of the underlying spatial process. In practice, however, this assumption is frequently violated. In fisheries, for example, sampling sites are often chosen to maximize expected catches, creating a stochastic dependence between…
Exaverio Chireshe, Retius Chifurira, Jesca Mercy Batidzirai, Knowledge Chinhamu + 1 more
Syndemics involving Human immunodeficiency virus (HIV) and other sexually transmitted infections (STIs) remain a major public health challenge in sub-Saharan Africa, and understanding their spatial and temporal dynamics is critical for effective interventions. Using data from two consecutive, population-based…
Chelsea R. Baker, Ivan Barilar, Leonardo S. de Araujo, Daniel M. Parker + 9 more
Objectives Our objective was to identify potential ‘hotspots’ of tuberculosis (TB) transmission by integrating pathogen genomic and geospatial data, including activity spaces where transmission may occur (e.g. community locations such as work, school, or social venues) in addition to residential locations. Methods We…
Fabian R. Ketwaroo, Matia H. Muller, James F. Saracco, Michael Schaub
Demographic processes in populations are inherently heterogeneous across both space and time. Many ecological models explicitly account for temporal heterogeneity in the demographic rates that govern these processes, but assume spatial homogeneity. Ignoring spatial heterogeneity can bias inference, limit predictive…
Jordan Downey, Avi Kenny
Key Messages1. The DISC (Different Individuals, Same Clusters) design is a practical hybrid between cohort and repeated cross-sectional (RCS) designs, in which the same clusters are sampled repeatedly, but within each cluster, different samples of individuals are collected at different time points. 2. This design can…
Authors not listed
People of color in the United States are disproportionately and unfairly exposed to air pollution. Equity-oriented scientific evaluations quantifying these disparities often use population-average exposure metrics to capture the overall inequality within a system. Utilizing these metrics involves choices about the…
Doreen Jehu-Appiah, Emmanuel Obeng-Gyasi
Large-scale population datasets are rarely generated via simple random sampling; instead, they reflect complex designs involving stratification, clustering, and unequal inclusion probabilities. While survey weights are provided to recover population-representative estimates, standard Bayesian Kernel Machine Regression…
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Atomistic simulations provide essential mechanistic insights into chemical processes, yet many important phenomena in chemistry and materials science occur on timescales that are inaccessible to molecular dynamics. Existing computational approaches force a choice between atomic resolution on relatively short timescales…
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Understanding how plants respond to dynamic and spatially variable stimuli is a key goal in plant sciences. Traditional imaging methods often involve a trade-off between environmental control and spatial resolution, limiting their ability to capture real-time responses in high resolution. Microfluidic technology…
Stefan Damerow, Ronny Kuhnert, Angelika Schaffrath Rosario, Johannes Lemcke
Background The panel `Health in Germany` has been established to gather nationwide health-related information, replacing cross-sectional surveys as primary data sources. However, panel designs involve multiple selection stages, potentially introducing additional nonresponse bias. This study aims to describe this…
Ravi Ranjan, Mridul K. Thomas
Ecological experiments often characterize species responses to environmental drivers by estimating parameters of well-known nonlinear functions. However, the standard experimental designs used for these experiments waste precious experimental resources by making measurements at uninformative driver levels. Classical…
Pei-Hsuan Hsieh
Randomization is a standard method in experimental research, yet its validity is not always guaranteed. This study introduces machine learning (ML) models as supplementary tools for validating participant randomization. A learning direction game with dichotomized scenarios was introduced, and both supervised and…
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Transition-state (TS) identification for bimolecular liquid-phase reactions is notoriously sensitive to the initial spatial arrangement of reactants, making automated searches difficult, especially in solvation where conformational effects dominate barrier heights. We address this gap with a fully automated, heuristic…
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In the United States, people of color are disproportionately and unjustly exposed to air pollution. Historically, environmental policy has emphasized aggregate emission reductions; yet major emission reduction scenarios do not sufficiently mitigate relative exposure disparities. Here, we show that without focusing on…
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Petroleum hydrocarbon contamination presents significant ecological and health challenges, driving the need for sustainable remediation approaches. This study evaluates the effectiveness of a biostimulant derived from valorized agricultural residues (maize and sorghum stalks) in enhancing indigenous…