1,585 research outputs found
Local Runup Amplification By Resonant Wave Interactions
Until now the analysis of long wave runup on a plane beach has been focused
on finding its maximum value, failing to capture the existence of resonant
regimes. One-dimensional numerical simulations in the framework of the
Nonlinear Shallow Water Equations (NSWE) are used to investigate the Boundary
Value Problem (BVP) for plane and non-trivial beaches. Monochromatic waves, as
well as virtual wave-gage recordings from real tsunami simulations, are used as
forcing conditions to the BVP. Resonant phenomena between the incident
wavelength and the beach slope are found to occur, which result in enhanced
runup of non-leading waves. The evolution of energy reveals the existence of a
quasi-periodic state for the case of sinusoidal waves, the energy level of
which, as well as the time required to reach that state, depend on the incident
wavelength for a given beach slope. Dispersion is found to slightly reduce the
value of maximum runup, but not to change the overall picture. Runup
amplification occurs for both leading elevation and depression waves.Comment: 10 pages, 7 Figures. Accepted to Physical Review Letters. Other
author's papers can be downloaded at http://www.lama.univ-savoie.fr/~dutykh
Learned Semantic Multi-Sensor Depth Map Fusion
Volumetric depth map fusion based on truncated signed distance functions has
become a standard method and is used in many 3D reconstruction pipelines. In
this paper, we are generalizing this classic method in multiple ways: 1)
Semantics: Semantic information enriches the scene representation and is
incorporated into the fusion process. 2) Multi-Sensor: Depth information can
originate from different sensors or algorithms with very different noise and
outlier statistics which are considered during data fusion. 3) Scene denoising
and completion: Sensors can fail to recover depth for certain materials and
light conditions, or data is missing due to occlusions. Our method denoises the
geometry, closes holes and computes a watertight surface for every semantic
class. 4) Learning: We propose a neural network reconstruction method that
unifies all these properties within a single powerful framework. Our method
learns sensor or algorithm properties jointly with semantic depth fusion and
scene completion and can also be used as an expert system, e.g. to unify the
strengths of various photometric stereo algorithms. Our approach is the first
to unify all these properties. Experimental evaluations on both synthetic and
real data sets demonstrate clear improvements.Comment: 11 pages, 7 figures, 2 tables, accepted for the 2nd Workshop on 3D
Reconstruction in the Wild (3DRW2019) in conjunction with ICCV201
Cryoablation and Immunotherapy: An Enthralling Synergy to Confront the Tumors.
Treatment of solid tumors by ablation techniques has gained momentum in the recent years due to their technical simplicity and reduced morbidity as juxtaposed to surgery. Cryoablation is one of such techniques, known for its uniqueness to destroy the tumors by freezing to lethal temperatures. Freezing the tumor locally and allowing it to remain in situ unleashes an array of tumor antigens to be exposed to the immune system, paving the way for the generation of anti-tumor immune responses. However, the immune responses triggered in most cases are insufficient to eradicate the tumors with systemic spread. Therefore, combination of cryoablation and immunotherapy is a new treatment strategy currently being evaluated for its efficacy, notably in patients with metastatic disease. This article examines the mechanistic fabric of cryoablation for the generation of an effective immune response against the tumors, and various possibilities of its combination with different immunotherapies that are capable of inducing exceptional therapeutic responses. The combinatorial treatment avenues discussed in this article if explored in sufficient profundity, could reach the pinnacle of future cancer medicine
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