Climate-Vegetation-Feedbacks as a Mechanism for Accelerated Climate Change: The onset of the African Humid Period

Paleo-environmental records and models indicate that the African Humid Period (AHPabruptly ended about 5000-4000 years before present (BP). Some proxies indicate alsan abrupt onset of the AHP between 14,000 and 11,000 BP. How important are local orbitaforcing, ice-sheet forcing, greenhouse gas forcing, and the reorganization of the AtlantiMeridional Overturning Circulation (AMOC) for changes in the African Monsoon/vegetatiosystem? Here we use transient simulations with climate-vegetation models of differencomplexity to identify the factors that control the onset of the African Monsoon/VegetationWe test the following hypothesis:(1) There is no indication for insolation-thresholds for the onset/break of the AHP.(2) Forcing from CO2/ice-sheets significantly controls the climate of North Africa.(3) CO2 fertilization contributes to the vegetation changes over North Africa.(4) A shutdown of the AMOC is as important as orbital insolation for the African Monsoon

Assessing the accuracy of δ<sup>18<\sup>O<sub>sw<?sub> estimates from corals: lessons from simple Monte Carlo simulations

EGU2008-A-04391 Paired measurements of δ18O and Sr/Ca in coral aragonite are routinely used for deriving estimates of δ18Osw and, by extension, sea surface salinity variations over the past centuries. However, in practice, the accuracy (or the error) of these estimates is often difficult to assess. Here, we use simulated proxy data and Monte-Carlo simulations to investigate the accuracy of δ18Osw estimates from paired coral δ18O and Sr/Ca measurements. First, we estimate expected values of coral Sr/Ca and δ18O from instrumental or reanalysis data of sea surface temperature (SST) and sea surface salinity (SSS). We then add the typical analytical errors onto the expected Sr/Ca (δ18O) data as random numbers and compute δ18Osw+error from the noisy proxy data for a 1000 sample Monte Carlo. From this simple Monte Carlo simulation, the range of correlation coefficients between δ18Osw+error and expected δ18Osw is estimated. As expected, we find that this range mainly depends on the magnitude of the actual SSS variations at a given site, as well as on the slope of the δ18Osw-SSS relationship. A comparison with real coral-based δ18Osw reconstructions from multiple sites indicates that correlations between reconstructed δ18Osw and instrumental SSS fall within the range of correlation coefficients predicted based on our Monte-Carlo simulation. Thus, our simple simulation exercise may help to assess the feasibility of δ18Osw and salinity reconstructions from corals in different climatic settings, provided that (i) some instrumental data of δ18Osw and/or SSS is available, and (ii) the slope of the δ18Osw-SSS relationship is known

Coyote Attacks on Humans, 1970-2015: Implications for Reducing the Risks

Beginning with the emerging pattern of urban and suburban coyotes (Canis latrans) attacking humans in southern California in the late 1970s, we analyzed information from reported attacks to better understand the factors contributing to changes in coyote behavior. We subsequently used updated data collected largely in urban and suburban environments in the United States and Canada during the past 30 years to develop strategies to reduce the risk of attacks. In the 1990s, increased incidents of coyote attacks were reported in states beyond California and in Canadian provinces. We documented 367 attacks on humans by coyotes from 1977 through 2015, of which 165 occurred in California. Of 348 total victims of coyote attack, 209 (60%) were adults, and 139 (40%) were children (age ≤10 years). Children (especially toddlers) are at greater risk of serious injury. The attacks exhibited seasonal patterns, with more occurring during the coyote breeding and pup-rearing season (March through August) than September through February. We reiterate management recommendations that, when enacted, have been demonstrated to effectively reduce risk of coyote attack in urban and suburban environments, and we note limitations of non-injurious hazing programs. We observed an apparent growing incidence of coyote attack on pets, an issue that we believe will drive coyote management policy at the local and state levels

MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose Estimation

Heatmap representations have formed the basis of human pose estimation systems for many years, and their extension to 3D has been a fruitful line of recent research. This includes 2.5D volumetric heatmaps, whose X and Y axes correspond to image space and Z to metric depth around the subject. To obtain metric-scale predictions, 2.5D methods need a separate post-processing step to resolve scale ambiguity. Further, they cannot localize body joints outside the image boundaries, leading to incomplete estimates for truncated images. To address these limitations, we propose metric-scale truncation-robust (MeTRo) volumetric heatmaps, whose dimensions are all defined in metric 3D space, instead of being aligned with image space. This reinterpretation of heatmap dimensions allows us to directly estimate complete, metric-scale poses without test-time knowledge of distance or relying on anthropometric heuristics, such as bone lengths. To further demonstrate the utility our representation, we present a differentiable combination of our 3D metric-scale heatmaps with 2D image-space ones to estimate absolute 3D pose (our MeTRAbs architecture). We find that supervision via absolute pose loss is crucial for accurate non-root-relative localization. Using a ResNet-50 backbone without further learned layers, we obtain state-of-the-art results on Human3.6M, MPI-INF-3DHP and MuPoTS-3D. Our code will be made publicly available to facilitate further research.Comment: See project page at https://vision.rwth-aachen.de/metrabs . Accepted for publication in the IEEE Transactions on Biometrics, Behavior, and Identity Science (TBIOM), Special Issue "Selected Best Works From Automated Face and Gesture Recognition 2020". Extended version of FG paper arXiv:2003.0295

Quantum Monte Carlo simulation of thin magnetic films

The stochastic series expansion quantum Monte Carlo method is used to study thin ferromagnetic films, described by a Heisenberg model including local anisotropies. The magnetization curve is calculated, and the results compared to Schwinger boson and many-body Green's function calculations. A transverse field is introduced in order to study the reorientation effect, in which the magnetization changes from out-of-plane to in-plane. Since the approximate theoretical approaches above differ significantly from each other, and the Monte Carlo method is free of systematic errors, the calculation provides an unbiased check of the approximate treatments. By studying quantum spin models with local anisotropies, varying spin size, and a transverse field, we also demonstrate the general applicability of the recent cluster-loop formulation of the stochastic series expansion quantum Monte Carlo method.Comment: 9 pages, 12 figure

Compressed vessels bias red blood cell partitioning at bifurcations in a hematocrit-dependent manner:implications in tumor blood flow

The tumor microenvironment is abnormal and associated with tumor tissue hypoxia, immunosuppression, and poor response to treatment. One important abnormality present in tumors is vessel compression. Vessel decompression has been shown to increase survival rates in animal models via enhanced and more homogeneous oxygenation. However, our knowledge of the biophysical mechanisms linking tumor decompression to improved tumor oxygenation is limited. In this study, we propose a computational model to investigate the impact of vessel compression on red blood cell (RBC) dynamics in tumor vascular networks. Our results demonstrate that vessel compression can alter RBC partitioning at bifurcations in a hematocrit-dependent and flow rate–independent manner. We identify RBC focusing due to cross-streamline migration as the mechanism responsible and characterize the spatiotemporal recovery dynamics controlling downstream partitioning. Based on this knowledge, we formulate a reduced-order model that will help future research to elucidate how these effects propagate at a whole vascular network level. These findings contribute to the mechanistic understanding of hemodilution in tumor vascular networks and oxygen homogenization following pharmacological solid tumor decompression

Metric-Scale Truncation-Robust Heatmaps for 3D Human Pose Estimation

Heatmap representations have formed the basis of 2D human pose estimation systems for many years, but their generalizations for 3D pose have only recently been considered. This includes 2.5D volumetric heatmaps, whose X and Y axes correspond to image space and the Z axis to metric depth around the subject. To obtain metric-scale predictions, these methods must include a separate, explicit post-processing step to resolve scale ambiguity. Further, they cannot encode body joint positions outside of the image boundaries, leading to incomplete pose estimates in case of image truncation. We address these limitations by proposing metric-scale truncation-robust (MeTRo) volumetric heatmaps, whose dimensions are defined in metric 3D space near the subject, instead of being aligned with image space. We train a fully-convolutional network to estimate such heatmaps from monocular RGB in an end-to-end manner. This reinterpretation of the heatmap dimensions allows us to estimate complete metric-scale poses without test-time knowledge of the focal length or person distance and without relying on anthropometric heuristics in post-processing. Furthermore, as the image space is decoupled from the heatmap space, the network can learn to reason about joints beyond the image boundary. Using ResNet-50 without any additional learned layers, we obtain state-of-the-art results on the Human3.6M and MPI-INF-3DHP benchmarks. As our method is simple and fast, it can become a useful component for real-time top-down multi-person pose estimation systems. We make our code publicly available to facilitate further research (see https://vision.rwth-aachen.de/metro-pose3d).Comment: Accepted for publication at the 2020 IEEE Conference on Automatic Face and Gesture Recognition (FG