pyUserCalc: A Revised Jupyter Notebook Calculator for Uranium-Series Disequilibria in Basalts

Meaningful analysis of uranium-series isotopic disequilibria in basaltic lavas relies on the use of complex forward numerical models like dynamic melting (McKenzie, 1985, https://doi.org/10.1016/0012- 821x(85)90001-9) and equilibrium porous flow (Spiegelman & Elliott, 1993, https://doi.org/10.1016/0012- 821x(93)90155-3). Historically, such models have either been solved analytically for simplified scenarios, such as constant melting rate or constant solid/melt trace element partitioning throughout the melting process, or have relied on incremental or numerical calculators with limited power to solve problems and/or restricted availability. The most public numerical solution to reactive porous flow, UserCalc (Spiegelman, 2000, https:// doi.org/10.1029/1999gc000030) was maintained on a private institutional server for nearly two decades, but that approach has been unsustainable in light of modern security concerns. Here, we present a more long-lasting solution to the problems of availability, model sophistication and flexibility, and long-term access in the form of a cloud-hosted, publicly available Jupyter notebook. Similar to UserCalc, the new notebook calculates U-series disequilibria during time-dependent, equilibrium partial melting in a one-dimensional porous flow regime where mass is conserved. In addition, we also provide a new disequilibrium transport model which has the same melt transport model as UserCalc, but approximates rate-limited diffusive exchange of nuclides between solid and melt using linear kinetics. The degree of disequilibrium during transport is controlled by a Damköhler number, allowing the full spectrum of equilibration models from complete fractional melting (Da = 0 ) to equilibrium transport (Da = ∞)

Magma migration and magmatic solitary waves in 3-D

Numerical studies of fluid flow in the mantle suggest that magma migration is an inherently time-dependent process that produces magmatic solitary waves from obstructions in melt flux. Previous work has considered one and two dimensional problems. Here we present the results of three dimensional calculations that utilize a new, efficient multigrid scheme. We demonstrate that one and two dimensional solitary waves are unstable and break up into sets of 3-D solitary waves which are perfectly spherical when propagating through a uniform porosity medium. While these waves are not solitons, their non-linear interactions are qualitatively similar. The solitary waves are highly opportunistic and establish efficient pathways for migration by linking up with nearby waves. When the initial condition is a random distribution of porosity, the porosity structure can organize into elongate, time-dependent channels formed from chains of solitary waves. These results are natural consequences of the assumptions that the matrix is permeable and viscously deformable. We suggest that solitary waves are likely to exist in the mantle and may contribute to the episodicity of mantle magmatism

A New Parameterization of Hydrous Mantle Melting

Modeling of melt formation and transport in all tectonic settings requires the inclusion of water, since water has large effects on mantle solidi as well as physical properties of liquids. To facilitate the inclusion of water in melting models this paper presents a new parameterization for melt fraction as a function of pressure, temperature, water content and modal cpx, based on knowledge gained from recent advances in the fields of thermodynamic modeling as well as experimental investigations of peridotite melting and hydrous equilibria. The parameterization is computationally efficient and can be modified easily as better experimental data become available. We compare it to other published parameterizations and test it insimple calculations of adiabatic decompression melting (mid-ocean ridge) and hydrous melting (subduction zone).Earth and Planetary Science

Modeling oscillations in connected glacial lakes

Mountain glaciers and ice sheets often host marginal and subglacial lakes that are hydraulically connected through subglacial drainage systems. These lakes exhibit complex dynamics that have been the subject of models for decades. Here we introduce and analyze a model for the evolution of glacial lakes connected by subglacial channels. Subglacial channel equations are supplied with effective pressure boundary conditions that are determined by a simple lake model. While the model can describe an arbitrary number of lakes, we solve it numerically with a finite element method for the case of two connected lakes. We examine the effect of relative lake size and spacing on the oscillations. Complex oscillations in the downstream lake are driven by discharge out of the upstream lake. These include multi-peaked and anti-phase filling–draining events. Similar filling–draining cycles have been observed on the Kennicott Glacier in Alaska and at the confluence of the Whillans and Mercer ice streams in West Antarctica. We further construct a simplified ordinary differential equation model that displays the same qualitative behavior as the full, spatially-dependent model. We analyze this model using dynamical systems theory to explain the appearance of filling–draining cycles as the meltwater supply varies

Investigating lava flow rheology using video analysis and numerical flow models

Lava rheology is a major control on lava flow behavior and a critical parameter in flow simulations, but is very difficult to measure at field conditions or correctly extrapolate from the lab scale. We present a new methodology for investigating lava rheology through a combination of controlled experiments, image analysis and numerical forward modeling. Our experimental setup, part of the Syracuse University Lava Project (http://lavaproject.syr.edu) includes a large furnace capable of melting up to 450 kg of basalt, at temperatures well above the basalt liquidus. The lava is poured onto either a tilted bed of sand or a steel channel to produce meter-long flows. This experimental setup is probably the only facility that allows such large scale controlled lava flows made of natural basaltic material. We document the motion of the lava using a high-resolution video camera placed directly above the flows, and the temperature using infrared probes and cameras. After collecting the footage, we analyze the images for lava deformation and compare with numerical forward-models to constrain the rheological parameters and laws which best describe the flowing lava. For the video analysis, we employ the technique of Differential Optical Flow, which uses the time-variations of the spatial gradients of the image intensity to estimate velocity between consecutive frames. An important benefit for using optical flow, compared with other velocimetry methods, is that it outputs a spatially coherent flow field rather than point measurements. We demonstrate that the optical flow results agree with other measures of the flow velocity, and estimate the error due to noise and time-variability to be under 30% of the measured velocity. Our forward-models are calculated by solving the Stokes flow equations on an unstructured finite-element mesh defined using the geometry of the observed flow itself. We explore a range of rheological parameters, including the lava's apparent viscosity, the power-law exponent m and the thermal activation energy. Our measurements of apparent viscosity agree well with predictions of the composition-based Shaw (1972) and GRD model (Giordano, Russell and Dingwell, 2008). We find that for the high-temperature portion of the flow a weakly shear-thinning or Newtonian rheology (m > 0.7) with an effective activation energy of B = 5500 J gives the best fit to the data. Our methodology is the first time that high-resolution optical flow analysis of flowing lava is combined with numerical flow models to constrain rheology. The methodology we present here can be used in field conditions to obtain in-situ information on lava rheology, without physical interaction with the flow and without being limited to point-wise, low strain-rate, local measurements currently available through the use of rotational viscometers in the field

Cold-induced changes in gene expression in brown adipose tissue, white adipose tissue and liver

Cold exposure imposes a metabolic challenge to mammals that is met by a coordinated response in different tissues to prevent hypothermia. This study reports a transcriptomic analysis in brown adipose tissue (BAT), white adipose (WAT) and liver of mice in response to 24 h cold exposure at 8°C. Expression of 1895 genes were significantly (P<0.05) up- or down-regulated more than two fold by cold exposure in all tissues but only 5 of these genes were shared by all three tissues, and only 19, 14 and 134 genes were common between WAT and BAT, WAT and liver, and BAT and liver, respectively. We confirmed using qRT-PCR, the increased expression of a number of characteristic BAT genes during cold exposure. In both BAT and the liver, the most common direction of change in gene expression was suppression (496 genes in BAT and 590 genes in liver). Gene ontology analysis revealed for the first time significant (P<0.05) down regulation in response to cold, of genes involved in oxidoreductase activity, lipid metabolic processes and protease inhibitor activity, in both BAT and liver, but not WAT. The results reveal an unexpected importance of down regulation of cytochrome P450 gene expression and apolipoprotein, in both BAT and liver, but not WAT, in response to cold exposure. Pathway analysis suggests a model in which down regulation of the nuclear transcription factors HNF4α and PPARα in both BAT and liver may orchestrate the down regulation of genes involved in lipoprotein and steroid metabolism as well as Phase I enzymes belonging to the cytochrome P450 group in response to cold stress in mice. We propose that the response to cold stress involves decreased gene expression in a range of cellular processes in order to maximise pathways involved in heat production

A combination of plasma phospholipid fatty acids and its association with incidence of type 2 diabetes: The EPIC-InterAct case-cohort study.

BACKGROUND: Combinations of multiple fatty acids may influence cardiometabolic risk more than single fatty acids. The association of a combination of fatty acids with incident type 2 diabetes (T2D) has not been evaluated. METHODS AND FINDINGS: We measured plasma phospholipid fatty acids by gas chromatography in 27,296 adults, including 12,132 incident cases of T2D, over the follow-up period between baseline (1991-1998) and 31 December 2007 in 8 European countries in EPIC-InterAct, a nested case-cohort study. The first principal component derived by principal component analysis of 27 individual fatty acids (mole percentage) was the main exposure (subsequently called the fatty acid pattern score [FA-pattern score]). The FA-pattern score was partly characterised by high concentrations of linoleic acid, stearic acid, odd-chain fatty acids, and very-long-chain saturated fatty acids and low concentrations of γ-linolenic acid, palmitic acid, and long-chain monounsaturated fatty acids, and it explained 16.1% of the overall variability of the 27 fatty acids. Based on country-specific Prentice-weighted Cox regression and random-effects meta-analysis, the FA-pattern score was associated with lower incident T2D. Comparing the top to the bottom fifth of the score, the hazard ratio of incident T2D was 0.23 (95% CI 0.19-0.29) adjusted for potential confounders and 0.37 (95% CI 0.27-0.50) further adjusted for metabolic risk factors. The association changed little after adjustment for individual fatty acids or fatty acid subclasses. In cross-sectional analyses relating the FA-pattern score to metabolic, genetic, and dietary factors, the FA-pattern score was inversely associated with adiposity, triglycerides, liver enzymes, C-reactive protein, a genetic score representing insulin resistance, and dietary intakes of soft drinks and alcohol and was positively associated with high-density-lipoprotein cholesterol and intakes of polyunsaturated fat, dietary fibre, and coffee (p < 0.05 each). Limitations include potential measurement error in the fatty acids and other model covariates and possible residual confounding. CONCLUSIONS: A combination of individual fatty acids, characterised by high concentrations of linoleic acid, odd-chain fatty acids, and very long-chain fatty acids, was associated with lower incidence of T2D. The specific fatty acid pattern may be influenced by metabolic, genetic, and dietary factors