Confinement of the Sun's interior magnetic field: some exact boundary-layer solutions

High-latitude laminar confinement of the Sun's interior magnetic field is shown to be possible, as originally proposed by Gough and McIntyre (1998) but contrary to a recent claim by Brun and Zahn (A&A 2006). Mean downwelling as weak as 2x10^-6cm/s -- gyroscopically pumped by turbulent stresses in the overlying convection zone and/or tachocline -- can hold the field in advective-diffusive balance within a confinement layer of thickness scale ~ 1.5Mm ~ 0.002 x (solar radius) while transmitting a retrograde torque to the Ferraro-constrained interior. The confinement layer sits at the base of the high-latitude tachocline, near the top of the radiative envelope and just above the `tachopause' marking the top of the helium settling layer. A family of exact, laminar, frictionless, axisymmetric confinement-layer solutions is obtained for uniform downwelling in the limit of strong rotation and stratification. A scale analysis shows that the flow is dynamically stable and the assumption of laminar flow realistic. The solution remains valid for downwelling values of the order of 10^-5cm/s but not much larger. This suggests that the confinement layer may be unable to accept a much larger mass throughput. Such a restriction would imply an upper limit on possible internal field strengths, perhaps of the order of hundreds of gauss, and would have implications also for ventilation and lithium burning. The solutions have interesting chirality properties not mentioned in the paper owing to space restrictions, but described at http://www.atmos-dynamics.damtp.cam.ac.uk/people/mem/papers/SQBO/solarfigure.htmlComment: 6 pages, 3 figures, to appear in conference proceedings: Unsolved Problems in Stellar Physic

Intervenções: rumo a um novo modelo de anacronismo renascentista

O texto apresenta uma nova visão dos anacronismos em pinturas renascentistas europeias a partir de duas teorias da historicidade da forma, performativa e substitucional. Nesta última, um artefato moderno é considerado uma antiguidade ao funcionar como substituto de um original perdido. O autor defende que ambos os modelos atuavam conjuntamente na arte renascentista europeia, e que essa dupla historicidade ainda não foi corretamente reconhecida pela historiografia da arte

Stability of spontaneous, correlated activity in mouse auditory cortex

Neural systems can be modeled as networks of functionally connected neural elements. The resulting network can be analyzed using mathematical tools from network science and graph theory to quantify the system's topological organization and to better understand its function. While the network-based approach is common in the analysis of large-scale neural systems probed by non-invasive neuroimaging, few studies have used network science to study the organization of networks reconstructed at the cellular level, and thus many very basic and fundamental questions remain unanswered. Here, we used two-photon calcium imaging to record spontaneous activity from the same set of cells in mouse auditory cortex over the course of several weeks. We reconstruct functional networks in which cells are linked to one another by edges weighted according to the correlation of their fluorescence traces. We show that the networks exhibit modular structure across multiple topological scales and that these multi-scale modules unfold as part of a hierarchy. We also show that, on average, network architecture becomes increasingly dissimilar over time, with similarity decaying monotonically with the distance (in time) between sessions. Finally, we show that a small fraction of cells maintain strongly-correlated activity over multiple days, forming a stable temporal core surrounded by a fluctuating and variable periphery. Our work provides a careful methodological blueprint for future studies of spontaneous activity measured by two-photon calcium imaging using cutting-edge computational methods and machine learning algorithms informed by explicit graphical models from network science. The methods are easily extended to additional datasets, opening the possibility of studying cellular level network organization of neural systems and how that organization is modulated by stimuli or altered in models of disease.Comment: 15 pages, 3 figure

LCM2021 – the UK Land Cover Map 2021

Land cover is a key environmental variable, underpinning widespread environmental research and decision making. The UK Centre for Ecology and Hydrology (UKCEH) has provided reliable land cover information since the early 1990s; this supports multiple scientific, government and commercial objectives. Recent advances in computation and satellite data availability have enabled annual UKCEH land cover maps since 2017. Here, we introduce the latest, annual UK Land Cover Map representing 2021 (LCM2021), and we describe its production and validation. LCM2021 methods replicate those of LCM2017 to LCM2020 with minor deviations in cloud-masking processes and training data sourcing to enhance accuracy. LCM2021 is based on the classification of satellite and spatial context data into 21 land cover or habitat classes, from which a product suite is derived. The production of LCM2021 involved three highly automated key stages: pre-processing of input data, image classification and production of the final data products. Google Earth Engine scripts were used to create an input data stack of satellite and context data. A set of training areas was created based on data harvested from historic UKCEH land cover maps. The training data were used to construct a random forest classifier, which yielded classified images. Compiled results were validated against 35 182 reference samples, with correspondence tables indicating variable class accuracy and an overall accuracy of 82.6 % for the 21-class data and 86.5 % at a 10-aggregated-classes level. The UK Land Cover Map product suite includes a set of raster products in various projections, thematic and spatial resolutions (10 m, 25 m and 1 km), and land–parcel or vector products. The data are provided in 21-class (all configurations) and aggregated 10-class (1 km raster products only) versions. All raster products are freely available for academic and non-commercial research. The data for Great Britain (GB) are provided in the British National Grid projection (EPSG: 27700) and the Northern Ireland (NI) data are in the TM75 Irish Grid (EPSG: 29903). Information on how to access the data is given in the “Data availability” section of the paper.</p

Peroxisome Proliferator-Activated Receptors Alpha, Beta, and Gamma mRNA and Protein Expression in Human Fetal Tissues

Peroxisome proliferator-activated receptors (PPARs) regulate lipid and glucose homeostasis, are targets of pharmaceuticals, and are also activated by environmental contaminants. Almost nothing is known about expression of PPARs during human fetal development. This study examines expression of PPARα, β, and γ mRNA and protein in human fetal tissues. With increasing fetal age, mRNA expression of PPARα and β increased in liver, but PPARβ decreased in heart and intestine, and PPARγ decreased in adrenal. Adult and fetal mean expression of PPARα, β, and γ mRNA did not differ in intestine, but expression was lower in fetal stomach and heart. PPARα and β mRNA in kidney and spleen, and PPARγ mRNA in lung and adrenal were lower in fetal versus adult. PPARγ in liver and PPARβ mRNA in thymus were higher in fetal versus adult. PPARα protein increased with fetal age in intestine and decreased in lung, kidney, and adrenal. PPARβ protein in adrenal and PPARγ in kidney decreased with fetal age. This study provides new information on expression of PPAR subtypes during human development and will be important in evaluating the potential for the developing human to respond to PPAR environmental or pharmaceutical agonists

The lesson of causal discovery algorithms for quantum correlations: Causal explanations of Bell-inequality violations require fine-tuning

An active area of research in the fields of machine learning and statistics is the development of causal discovery algorithms, the purpose of which is to infer the causal relations that hold among a set of variables from the correlations that these exhibit. We apply some of these algorithms to the correlations that arise for entangled quantum systems. We show that they cannot distinguish correlations that satisfy Bell inequalities from correlations that violate Bell inequalities, and consequently that they cannot do justice to the challenges of explaining certain quantum correlations causally. Nonetheless, by adapting the conceptual tools of causal inference, we can show that any attempt to provide a causal explanation of nonsignalling correlations that violate a Bell inequality must contradict a core principle of these algorithms, namely, that an observed statistical independence between variables should not be explained by fine-tuning of the causal parameters. In particular, we demonstrate the need for such fine-tuning for most of the causal mechanisms that have been proposed to underlie Bell correlations, including superluminal causal influences, superdeterminism (that is, a denial of freedom of choice of settings), and retrocausal influences which do not introduce causal cycles.Comment: 29 pages, 28 figs. New in v2: a section presenting in detail our characterization of Bell's theorem as a contradiction arising from (i) the framework of causal models, (ii) the principle of no fine-tuning, and (iii) certain operational features of quantum theory; a section explaining why a denial of hidden variables affords even fewer opportunities for causal explanations of quantum correlation