796 research outputs found
Escaping Plato's Cave using Adversarial Training: 3D Shape From Unstructured 2D Image Collections
We introduce PLATONICGAN to discover the 3D structure of an object class from an unstructured collection of 2D
images, i. e., neither any relation between the images is available nor additional information about the images is known.
The key idea is to train a deep neural network to generate
3D shapes which rendered to images are indistinguishable
from ground truth images (for a discriminator) under various camera models (i. e., rendering layers) and camera
poses. Discriminating 2D images instead of 3D shapes allows tapping into unstructured 2D photo collections instead
of relying on curated (e.g., aligned, annotated, etc.) 3D data
sets. To establish constraints between 2D image observation
and their 3D interpretation, we suggest a family of rendering
layers that are effectively differentiable. This family includes
visual hull, absorption-only (akin to x-ray), and emissionabsorption. We can successfully reconstruct 3D shapes from
unstructured 2D images and extensively evaluate PLATONICGAN on a range of synthetic and real data sets achieving
consistent improvements over baseline methods. We can also
show that our method with additional 3D supervision further
improves result quality and even surpasses the performance
of 3D supervised methods
CamP: Camera Preconditioning for Neural Radiance Fields
Neural Radiance Fields (NeRF) can be optimized to obtain high-fidelity 3D
scene reconstructions of objects and large-scale scenes. However, NeRFs require
accurate camera parameters as input -- inaccurate camera parameters result in
blurry renderings. Extrinsic and intrinsic camera parameters are usually
estimated using Structure-from-Motion (SfM) methods as a pre-processing step to
NeRF, but these techniques rarely yield perfect estimates. Thus, prior works
have proposed jointly optimizing camera parameters alongside a NeRF, but these
methods are prone to local minima in challenging settings. In this work, we
analyze how different camera parameterizations affect this joint optimization
problem, and observe that standard parameterizations exhibit large differences
in magnitude with respect to small perturbations, which can lead to an
ill-conditioned optimization problem. We propose using a proxy problem to
compute a whitening transform that eliminates the correlation between camera
parameters and normalizes their effects, and we propose to use this transform
as a preconditioner for the camera parameters during joint optimization. Our
preconditioned camera optimization significantly improves reconstruction
quality on scenes from the Mip-NeRF 360 dataset: we reduce error rates (RMSE)
by 67% compared to state-of-the-art NeRF approaches that do not optimize for
cameras like Zip-NeRF, and by 29% relative to state-of-the-art joint
optimization approaches using the camera parameterization of SCNeRF. Our
approach is easy to implement, does not significantly increase runtime, can be
applied to a wide variety of camera parameterizations, and can
straightforwardly be incorporated into other NeRF-like models.Comment: SIGGRAPH Asia 2023, Project page: https://camp-nerf.github.i
Red blood cell invasion by Plasmodium vivax: Structural basis for DBP engagement of DARC
Plasmodium parasites use specialized ligands which bind to red blood cell (RBC) receptors during invasion. Defining the mechanism of receptor recognition is essential for the design of interventions against malaria. Here, we present the structural basis for Duffy antigen (DARC) engagement by P. vivax Duffy binding protein (DBP). We used NMR to map the core region of the DARC ectodomain contacted by the receptor binding domain of DBP (DBP-RII) and solved two distinct crystal structures of DBP-RII bound to this core region of DARC. Isothermal titration calorimetry studies show these structures are part of a multi-step binding pathway, and individual point mutations of residues contacting DARC result in a complete loss of RBC binding by DBP-RII. Two DBP-RII molecules sandwich either one or two DARC ectodomains, creating distinct heterotrimeric and heterotetrameric architectures. The DARC N-terminus forms an amphipathic helix upon DBP-RII binding. The studies reveal a receptor binding pocket in DBP and critical contacts in DARC, reveal novel targets for intervention, and suggest that targeting the critical DARC binding sites will lead to potent disruption of RBC engagement as complex assembly is dependent on DARC binding. These results allow for models to examine inter-species infection barriers, Plasmodium immune evasion mechanisms, P. knowlesi receptor-ligand specificity, and mechanisms of naturally acquired P. vivax immunity. The step-wise binding model identifies a possible mechanism by which signaling pathways could be activated during invasion. It is anticipated that the structural basis of DBP host-cell engagement will enable development of rational therapeutics targeting this interaction
Markov dynamic models for long-timescale protein motion
Molecular dynamics (MD) simulation is a well-established method for studying protein motion at the atomic scale. However, it is computationally intensive and generates massive amounts of data. One way of addressing the dual challenges of computation efficiency and data analysis is to construct simplified models of long-timescale protein motion from MD simulation data. In this direction, we propose to use Markov models with hidden states, in which the Markovian states represent potentially overlapping probabilistic distributions over protein conformations. We also propose a principled criterion for evaluating the quality of a model by its ability to predict long-timescale protein motions. Our method was tested on 2D synthetic energy landscapes and two extensively studied peptides, alanine dipeptide and the villin headpiece subdomain (HP-35 NleNle). One interesting finding is that although a widely accepted model of alanine dipeptide contains six states, a simpler model with only three states is equally good for predicting long-timescale motions. We also used the constructed Markov models to estimate important kinetic and dynamic quantities for protein folding, in particular, mean first-passage time. The results are consistent with available experimental measurements
Two-domains bulklike Fermi surface of Ag films deposited onto Si(111)-(7x7)
Thick metallic silver films have been deposited onto Si(111)-(7x7) substrates
at room temperature. Their electronic properties have been studied by using
angle resolved photoelectron spectroscopy (ARPES). In addition to the
electronic band dispersion along the high-symmetry directions, the Fermi
surface topology of the grown films has been investigated. Using ARPES, the
spectral weight distribution at the Fermi level throughout large portions of
the reciprocal space has been determined at particular perpendicular
electron-momentum values. Systematically, the contours of the Fermi surface of
these films reflected a sixfold symmetry instead of the threefold symmetry of
Ag single crystal. This loss of symmetry has been attributed to the fact that
these films appear to be composed by two sets of domains rotated 60 from
each other. Extra, photoemission features at the Fermi level were also
detected, which have been attributed to the presence of surface states and
\textit{sp}-quantum states. The dimensionality of the Fermi surface of these
films has been analyzed studying the dependence of the Fermi surface contours
with the incident photon energy. The behavior of these contours measured at
particular points along the Ag L high-symmetry direction puts forward
the three-dimensional character of the electronic structure of the films
investigated.Comment: 10 pages, 12 figures, submitted to Physical Review
ReconFusion: 3D Reconstruction with Diffusion Priors
3D reconstruction methods such as Neural Radiance Fields (NeRFs) excel at
rendering photorealistic novel views of complex scenes. However, recovering a
high-quality NeRF typically requires tens to hundreds of input images,
resulting in a time-consuming capture process. We present ReconFusion to
reconstruct real-world scenes using only a few photos. Our approach leverages a
diffusion prior for novel view synthesis, trained on synthetic and multiview
datasets, which regularizes a NeRF-based 3D reconstruction pipeline at novel
camera poses beyond those captured by the set of input images. Our method
synthesizes realistic geometry and texture in underconstrained regions while
preserving the appearance of observed regions. We perform an extensive
evaluation across various real-world datasets, including forward-facing and
360-degree scenes, demonstrating significant performance improvements over
previous few-view NeRF reconstruction approaches.Comment: Project page: https://reconfusion.github.io
Evaluating signatures of glacial refugia for North Atlantic benthic marine taxa
A goal of phylogeography is to relate patterns of genetic differentiation to
potential historical geographic isolating events. Quaternary glaciations, particularly the one culminating in the Last Glacial Maximum ;21 ka (thousands of years ago), greatly affected the distributions and population sizes of temperate marine species as their ranges retreated southward to escape ice sheets. Traditional genetic models of glacial refugia and routes of
recolonization include these predictions: low genetic diversity in formerly glaciated areas, with a small number of alleles/ haplotypes dominating disproportionately large areas, and high diversity including ‘‘private’’ alleles in glacial refugia. In the Northern Hemisphere, low
diversity in the north and high diversity in the south are expected. This simple model does not account for the possibility of populations surviving in relatively small northern periglacial refugia. If these periglacial populations experienced extreme bottlenecks, they could have the low genetic diversity expected in recolonized areas with no refugia, but should have more endemic diversity (private alleles) than recently recolonized areas. This review examines
evidence of putative glacial refugia for eight benthic marine taxa in the temperate North Atlantic. All data sets were reanalyzed to allow direct comparisons between geographic patterns of genetic diversity and distribution of particular clades and haplotypes including private alleles. We contend that for marine organisms the genetic signatures of northern
periglacial and southern refugia can be distinguished from one another. There is evidence for several periglacial refugia in northern latitudes, giving credence to recent climatic reconstructions with less extensive glaciation
Simulations of energetic beam deposition: from picoseconds to seconds
We present a new method for simulating crystal growth by energetic beam
deposition. The method combines a Kinetic Monte-Carlo simulation for the
thermal surface diffusion with a small scale molecular dynamics simulation of
every single deposition event. We have implemented the method using the
effective medium theory as a model potential for the atomic interactions, and
present simulations for Ag/Ag(111) and Pt/Pt(111) for incoming energies up to
35 eV. The method is capable of following the growth of several monolayers at
realistic growth rates of 1 monolayer per second, correctly accounting for both
energy-induced atomic mobility and thermal surface diffusion. We find that the
energy influences island and step densities and can induce layer-by-layer
growth. We find an optimal energy for layer-by-layer growth (25 eV for Ag),
which correlates with where the net impact-induced downward interlayer
transport is at a maximum. A high step density is needed for energy induced
layer-by-layer growth, hence the effect dies away at increased temperatures,
where thermal surface diffusion reduces the step density. As part of the
development of the method, we present molecular dynamics simulations of single
atom-surface collisions on flat parts of the surface and near straight steps,
we identify microscopic mechanisms by which the energy influences the growth,
and we discuss the nature of the energy-induced atomic mobility
Splenomegaly, elevated alkaline phosphatase and mutations in the SRSF2/ASXL1/RUNX1 gene panel are strong adverse prognostic markers in patients with systemic mastocytosis
We evaluated the impact of clinical and molecular characteristics on overall survival (OS) in 108 patients with indolent (n=41) and advanced SM (advSM, n=67). Organomegaly was measured by magnetic resonance imaging (MRI)-based volumetry of liver and spleen. In multivariate analysis of all patients, an increased spleen volume greater than or equal to450?ml (hazard ratio [HR], 5.2; 95% confidence interval [CI], [2.1–13.0]; P=0.003) and an elevated alkaline phosphatase (AP; HR 5.0 [1.1–22.2]; P=0.02) were associated with adverse OS. The 3-year OS was 100, 77, and 39%, respectively (P<0.0001), for patients with 0 (low-risk, n=37), 1 (intermediate-risk, n=32) or 2 (high-risk, n=39) parameters. For advSM patients with fully available clinical and molecular data (n=60), univariate analysis identified splenomegaly greater than or equal to1200?ml, elevated AP and mutations in the SRSF2/ASXL1/RUNX1 (S/A/R) gene panel as significant prognostic markers. In multivariate analysis, mutations in S/A/R (HR, 3.2 [1.1–9.6]; P=0.01) and elevated AP (HR 2.6 [1.0–7.1]; P=0.03) remained predictive adverse prognostic markers for OS. The 3-year OS was 76% and 38%, respectively (P=0.0003), for patients with 0-1 (intermediate-risk, n=28) or 2 (high-risk, n=32) parameters. We conclude that splenomegaly, elevated AP and mutations in the S/A/R gene panel are independent of the WHO classification and provide the most relevant prognostic information in SM patient
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