Finite element surface registration incorporating curvature, volume preservation, and statistical model information

We present a novel method for nonrigid registration of 3D surfaces and images. The method can be used to register surfaces by means of their distance images, or to register medical images directly. It is formulated as a minimization problem of a sum of several terms representing the desired properties of a registration result: smoothness, volume preservation, matching of the surface, its curvature, and possible other feature images, as well as consistency with previous registration results of similar objects, represented by a statistical deformation model. While most of these concepts are already known, we present a coherent continuous formulation of these constraints, including the statistical deformation model. This continuous formulation renders the registration method independent of its discretization. The finite element discretization we present is, while independent of the registration functional, the second main contribution of this paper. The local discontinuous Galerkin method has not previously been used in image registration, and it provides an efficient and general framework to discretize each of the terms of our functional. Computational efficiency and modest memory consumption are achieved thanks to parallelization and locally adaptive mesh refinement. This allows for the first time the use of otherwise prohibitively large 3D statistical deformation models

The control of short-term ice mélange weakening episodes on calving activity at major Greenland outlet glaciers

The dense mixture of iceberg of various sizes and sea ice observed in many of Greenland's fjords, called ice mélange (sikussak in Greenlandic), has been shown to have a significant impact on the dynamics of several Greenland tidewater glaciers, mainly through the seasonal support it provides to the glacier terminus in winter. However, a clear understanding of shorter-term ice mélange dynamics is still lacking, mainly due to the high complexity and variability of the processes at play at the ice–ocean boundary. In this study, we use a combination of Sentinel-1 radar and Sentinel-2 optical satellite imagery to investigate in detail intra-seasonal ice mélange dynamics and its link to calving activity at three major outlet glaciers: Kangerdlugssuaq Glacier, Helheim Glacier and Sermeq Kujalleq in Kangia (Jakobshavn Isbræ). In those fjords, we identified recurrent ice mélange weakening (IMW) episodes consisting of the up-fjord propagation of a discontinuity between jam-packed and weaker ice mélange towards the glacier terminus. At a late stage, i.e., when the IMW front approaches the glacier terminus, these episodes were often correlated with the occurrence of large-scale calving events. The IMW process is particularly visible at the front of Kangerdlugssuaq Glacier and presents a cyclic behavior, such that we further analyzed IMW dynamics during the June–November period from 2018 to 2021 at this location. Throughout this period, we detected 30 IMW episodes with a recurrence time of 24 d, propagating over a median distance of 5.9 km and for 17 d, resulting in a median propagation speed of 400 m d−1. We found that 87 % of the IMW episodes occurred prior to a calving event visible in spaceborne observations and that ∼75 % of all detected calving events were preceded by an IMW episode. These results therefore present the IMW process as a clear control on the calving activity of Kangerdlugssuaq Glacier. Finally, using a simple numerical model for ice mélange motion, we showed that a slightly biased random motion of ice floes without fluctuating external forcing can reproduce IMW events and their cyclic influence and explain observed propagation speeds. These results further support our observations in characterizing the IMW process as self-sustained through the existence of an IMW–calving feedback. This study therefore highlights the importance of short-term ice mélange dynamics in the longer-term evolution of Greenland outlet glaciers

Morphable Face Models - An Open Framework

In this paper, we present a novel open-source pipeline for face registration based on Gaussian processes as well as an application to face image analysis. Non-rigid registration of faces is significant for many applications in computer vision, such as the construction of 3D Morphable face models (3DMMs). Gaussian Process Morphable Models (GPMMs) unify a variety of non-rigid deformation models with B-splines and PCA models as examples. GPMM separate problem specific requirements from the registration algorithm by incorporating domain-specific adaptions as a prior model. The novelties of this paper are the following: (i) We present a strategy and modeling technique for face registration that considers symmetry, multi-scale and spatially-varying details. The registration is applied to neutral faces and facial expressions. (ii) We release an open-source software framework for registration and model-building, demonstrated on the publicly available BU3D-FE database. The released pipeline also contains an implementation of an Analysis-by-Synthesis model adaption of 2D face images, tested on the Multi-PIE and LFW database. This enables the community to reproduce, evaluate and compare the individual steps of registration to model-building and 3D/2D model fitting. (iii) Along with the framework release, we publish a new version of the Basel Face Model (BFM-2017) with an improved age distribution and an additional facial expression model

Chemical Information Media in the Chemistry Lecture Hall: A Comparative Assessment of Two Online Encyclopedias

The chemistry encyclopedia Römpp Online and the German universal encyclopedia Wikipedia were assessed by first-year university students on the basis of a set of 30 articles about chemical thermodynamics. Criteria with regard to both content and form were applied in the comparison; 619 ratings (48% participation rate) were returned. While both encyclopedias obtained very good marks and performed nearly equally with regard to their accuracy, the average overall mark for Wikipedia was better than for Römpp Online, which obtained lower marks with regard to completeness and length. Analysis of the results and participants' comments shows that students attach importance to completeness, length and comprehensibility rather than accuracy, and also attribute less value to the availability of sources which validate an encyclopedia article. Both encyclopedias can be promoted as a starting reference to access a topic in chemistry. However, it is recommended that instructors should insist that students do not rely solely on encyclopedia texts, but use and cite primary literature in their reports

Observational constraints on the sensitivity of two calving glaciers to external forcings

Future mass loss projections of the Greenland ice sheet require understanding of the processes at a glacier terminus, especially of iceberg calving. We present detailed and high-rate terrestrial radar interferometer observations of Eqip Sermia and Bowdoin Glacier, two outlet glaciers in Greenland with comparable dimensions and investigate iceberg calving, surface elevation, velocity, strain rates and their links to air temperature, tides and topography. The results reveal that the two glaciers exhibit very different flow and calving behaviour on different timescales. Ice flow driven by a steep surface slope with several topographic steps leads to high velocities, areas of extension and intense crevassing, which triggers frequent but small calving events independent of local velocity gradients. In contrast, ice flow under smooth surface slopes leaves the ice relatively intact, such that sporadic large-scale calving events dominate, which initiate in areas with high shearing. Flow acceleration caused by enhanced meltwater input and tidal velocity variations were observed for terminus sections close to floatation. Firmly grounded terminus sections showed no tidal signal and a weak short-term reaction to air temperature. These results demonstrate reaction timescales to external forcings from hours to months, which are, however, strongly dependent on local terminus geometry

Deep learning speeds up ice flow modelling by several orders of magnitude

This paper introduces the Instructed Glacier Model (IGM) – a model that simulates ice dynamics, mass balance and its coupling to predict the evolution of glaciers, icefields or ice sheets. The novelty of IGM is that it models the ice flow by a Convolutional Neural Network, which is trained from data generated with hybrid SIA + SSA or Stokes ice flow models. By doing so, the most computationally demanding model component is substituted by a cheap emulator. Once trained with representative data, we demonstrate that IGM permits to model mountain glaciers up to 1000 × faster than Stokes ones on Central Processing Units (CPU) with fidelity levels above 90% in terms of ice flow solutions leading to nearly identical transient thickness evolution. Switching to the GPU often permits additional significant speed-ups, especially when emulating Stokes dynamics or/and modelling at high spatial resolution. IGM is an open-source Python code which deals with two-dimensional (2-D) gridded input and output data. Together with a companion library of trained ice flow emulators, IGM permits user-friendly, highly efficient and mechanically state-of-the-art glacier and icefields simulations

Probabilistic Joint Face-Skull Modelling for Facial Reconstruction

We present a novel method for co-registration of two independent statistical shape models. We solve the problem of aligning a face model to a skull model with stochastic optimization based on Markov Chain Monte Carlo (MCMC). We create a probabilistic joint face-skull model and show how to obtain a distribution of plausible face shapes given a skull shape. Due to environmental and genetic factors, there exists a distribution of possible face shapes arising from the same skull. We pose facial reconstruction as a conditional distribution of plausible face shapes given a skull shape. Because it is very difficult to obtain the distribution directly from MRI or CT data, we create a dataset of artificial face-skull pairs. To do this, we propose to combine three data sources of independent origin to model the joint face-skull distribution: a face shape model, a skull shape model and tissue depth marker information. For a given skull, we compute the posterior distribution of faces matching the tissue depth distribution with Metropolis-Hastings. We estimate the joint faceskull distribution from samples of the posterior. To find faces matching to an unknown skull, we estimate the probability of the face under the joint faceskull model. To our knowledge, we are the first to provide a whole distribution of plausible faces arising from a skull instead of only a single reconstruction. We show how the face-skull model can be used to rank a face dataset and on average successfully identify the correct match in top 30%. The face ranking even works when obtaining the face shapes from 2D images. We furthermore show how the face-skull model can be useful to estimate the skull position in an MR-image

Methodology for measuring photonuclear reaction cross sections with an electron accelerator based on Bayesian analysis

Accurate measurements of photonuclear reaction cross sections are crucial for a number of applications, including radiation shielding design, absorbed dose calculations, reactor physics and engineering, nuclear safeguard and inspection, astrophysics, and nuclear medicine. Primarily motivated by the study of the production of selected radionuclides with high-energy photon beams (mainly 225Ac, 47Sc, and 67Cu), we have established a methodology for the measurement of photonuclear reaction cross sections with the microtron accelerator available at the Swiss Federal Institute of Metrology (METAS). The proposed methodology is based on the measurement of the produced activity with a High Purity Germanium (HPGe) spectrometer and on the knowledge of the photon fluence spectrum through Monte Carlo simulations. The data analysis is performed by applying a Bayesian fitting procedure to the experimental data and by assuming a functional trend of the cross section, in our case a Breit-Wigner function. We validated the entire methodology by measuring a well-established photonuclear cross section, namely the 197Au({\gamma},n)196Au reaction. The results are consistent with those reported in the literature

Bi-directional modulation of AMPA receptor unitary conductance by synaptic activity

BACKGROUND: Knowledge of how synapses alter their efficiency of communication is central to the understanding of learning and memory. The most extensively studied forms of synaptic plasticity are long-term potentiation (LTP) and its counterpart long-term depression (LTD) of AMPA receptor-mediated synaptic transmission. In the CA1 region of the hippocampus, it has been shown that LTP often involves a rapid increase in the unitary conductance of AMPA receptor channels. However, LTP can also occur in the absence of any alteration in AMPA receptor unitary conductance. In the present study we have used whole-cell dendritic recording, failures analysis and non-stationary fluctuation analysis to investigate the mechanism of depotentiation of LTP. RESULTS: We find that when LTP involves an increase in unitary conductance, subsequent depotentiation invariably involves the return of unitary conductance to pre-LTP values. In contrast, when LTP does not involve a change in unitary conductance then depotentiation also occurs in the absence of any change in unitary conductance, indicating a reduction in the number of activated receptors as the most likely mechanism. CONCLUSIONS: These data show that unitary conductance can be bi-directionally modified by synaptic activity. Furthermore, there are at least two distinct mechanisms to restore synaptic strength from a potentiated state, which depend upon the mechanism of the previous potentiation