Displacement/Length Scaling Relationships for Normal Faults; a Review, Critique, and Revised Compilation

The relationship between normal fault displacement (D) and length (L) varies due to numerous factors, including fault size, maturity, basin tectonic history, and host rock lithology. Understanding how fault D and L relate is useful, given related scaling laws are often used to help refine interpretations of often incomplete, subsurface datasets, which has implications for hydrocarbon and low-carbon energy applications. Here we provide a review of D/L scaling laws for normal faults, discuss factors that could influence these relationships, including both geological factors and errors in measurement, and provide a critique of previously published D/L databases. We then present our newly assembled database of 4059 normal faults from 66 sources that include explicit information on: 1) fault length and displacement, 2) host rock lithology, 3) host basin tectonic history, and 4) maturity, as well as fault D and L through time when these data are available. We find an overall scaling law of D = 0.3L0.92, which is similar to previously published scaling equations and that varies in response to the aforementioned geological factors. Our data show that small faults (<1 m length) tend to be over-displaced compared to larger faults, active faults tend to be over-displaced compared to inactive faults, and faults with stiffer host rock lithologies, like igneous and carbonate rocks, tend to be under-displaced with respect to faults within softer, more compliant host rocks, like clastic sedimentary rocks. Our dynamic D/L through time data show that faults follow the hybrid fault growth model, i.e., they initially lengthen, during which time they will appear under-displaced, before accumulating displacement. To the best of our knowledge, this is the first comprehensive, integrated, critical study of D/L scaling laws for normal faults and the factors influencing their growth. These revised relationships can now be utilized for predicting fault length or displacement when only one variable is available and provide the basis for general understanding D/L scaling laws in the context of normal fault growth. This underpinning database is open-access and is available for analysis and manipulation by the broader structural geology community.publishedVersio

Statistics of extremal intensities for Gaussian interfaces

The extremal Fourier intensities are studied for stationary Edwards-Wilkinson-type, Gaussian, interfaces with power-law dispersion. We calculate the probability distribution of the maximal intensity and find that, generically, it does not coincide with the distribution of the integrated power spectrum (i.e. roughness of the surface), nor does it obey any of the known extreme statistics limit distributions. The Fisher-Tippett-Gumbel limit distribution is, however, recovered in three cases: (i) in the non-dispersive (white noise) limit, (ii) for high dimensions, and (iii) when only short-wavelength modes are kept. In the last two cases the limit distribution emerges in novel scenarios.Comment: 15 pages, including 7 ps figure

Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits : A Multi-Ethnic Meta-Analysis of 45,891 Individuals

J. Kaprio, S. Ripatti ja M.-L. Lokki työryhmien jäseniä.Peer reviewe

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Cyber Literacy for GIScience : Toward Formalizing Geospatial Computing Education

The unprecedented availability of geospatial data and technologies is driving innovation and discovery but not without the risk of losing focus on the geographic foundations of space and place in this vast “cyber sea” of data and technology. There is a pressing need to educate a new generation of scientists and citizens who understand how space and place matter in the real world and who understand and can keep pace with technological advancements in the computational world. We define cyberliteracy for GIScience (cyberGIScience literacy) and outline eight core areas that serve as a framework for establishing the essential abilities and foundational knowledge necessary to navigate and thrive in this new technologically rich world. The core areas are arranged to provide multiple dimensions of learning ranging from a technological focus to a problem solving focus or a focus on GIScience or computational science. We establish a competency matrix as a means of assessing and evaluating levels of cyberGIScience literacy across the eight core areas. We outline plans to catalyze the collaborative development and sharing of instructional materials to embed cyberGIScience literacy in the classroom and begin to realize a cyberliterate citizenry and academe

Cyber Literacy for GIScience : Toward Formalizing Geospatial Computing Education

The unprecedented availability of geospatial data and technologies is driving innovation and discovery but not without the risk of losing focus on the geographic foundations of space and place in this vast “cyber sea” of data and technology. There is a pressing need to educate a new generation of scientists and citizens who understand how space and place matter in the real world and who understand and can keep pace with technological advancements in the computational world. We define cyberliteracy for GIScience (cyberGIScience literacy) and outline eight core areas that serve as a framework for establishing the essential abilities and foundational knowledge necessary to navigate and thrive in this new technologically rich world. The core areas are arranged to provide multiple dimensions of learning ranging from a technological focus to a problem solving focus or a focus on GIScience or computational science. We establish a competency matrix as a means of assessing and evaluating levels of cyberGIScience literacy across the eight core areas. We outline plans to catalyze the collaborative development and sharing of instructional materials to embed cyberGIScience literacy in the classroom and begin to realize a cyberliterate citizenry and academe

A genetic linkage map of the rat derived from recombinant inbred strains.

We have constructed a genetic linkage map in the rat by analyzing the strain distribution patterns of 500 genetic markers in a large set of recombinant inbred strains derived from the spontaneously hypertensive rat and the Brown-Norway rat (HXB and BXH recombinant inbred strains). 454 of the markers could be assigned to specific chromosomes, and the amount of genome covered by the mapped markers was estimated to be 1151 centimorgans. By including a variety of morphologic, biochemical, immunogenetic, and molecular markers, the current map integrates and extends existing linkage data and should facilitate rat gene mapping and genetic studies of hypertension and other complex phenotypes of interest in the HXB and BXH recombinant inbred strains.Journal ArticleResearch Support, Non-U.S. Gov'tinfo:eu-repo/semantics/publishe

Overlapping genetic architecture between Parkinson disease and melanoma

Epidemiologic studies have reported inconsistent results regarding an association between Parkinson disease (PD) and cutaneous melanoma (melanoma). Identifying shared genetic architecture between these diseases can support epidemiologic findings and identify common risk genes and biological pathways. Here, we apply polygenic, linkage disequilibrium-informed methods to the largest available case-control, genome-wide association study summary statistic data for melanoma and PD. We identify positive and significant genetic correlation (correlation: 0.17, 95% CI 0.10-0.24; P = 4.09 x 10(-06)) between melanoma and PD. We further demonstrate melanoma and PD-inferred gene expression to overlap across tissues (correlation: 0.14, 95% CI 0.06 to 0.22; P = 7.87 x 10(-04)) and highlight seven genes including PIEZO1, TRAPPC2L, and SOX6 as potential mediators of the genetic correlation between melanoma and PD. These findings demonstrate specific, shared genetic architecture between PD and melanoma that manifests at the level of gene expression.Hereditary cancer genetic