Active nonrigid ICP algorithm

© 2015 IEEE.The problem of fitting a 3D facial model to a 3D mesh has received a lot of attention the past 15-20 years. The majority of the techniques fit a general model consisting of a simple parameterisable surface or a mean 3D facial shape. The drawback of this approach is that is rather difficult to describe the non-rigid aspect of the face using just a single facial model. One way to capture the 3D facial deformations is by means of a statistical 3D model of the face or its parts. This is particularly evident when we want to capture the deformations of the mouth region. Even though statistical models of face are generally applied for modelling facial intensity, there are few approaches that fit a statistical model of 3D faces. In this paper, in order to capture and describe the non-rigid nature of facial surfaces we build a part-based statistical model of the 3D facial surface and we combine it with non-rigid iterative closest point algorithms. We show that the proposed algorithm largely outperforms state-of-the-art algorithms for 3D face fitting and alignment especially when it comes to the description of the mouth region

Intensity interferometry of single x-ray pulses from a synchrotron storage ring

We report on measurements of second-order intensity correlations at the high brilliance storage ring PETRA III using a prototype of the newly developed Adaptive Gain Integrating Pixel Detector (AGIPD). The detector recorded individual synchrotron radiation pulses with an x-ray photon energy of 14.4 keV and repetition rate of about 5 MHz. The second-order intensity correlation function was measured simultaneously at different spatial separations that allowed to determine the transverse coherence length at these x-ray energies. The measured values are in a good agreement with theoretical simulations based on the Gaussian Schell-model.Comment: 16 pages, 6 figures, 42 reference

Green composites of poly(3-hydroxybutyrate) containing graphene nanoplatelets with desirable electrical conductivity and oxygen barrier properties

Poly(3-hydroxybutyrate), a green polymer originating from prokaryotic microbes, has been used to prepare composites with graphene nanoplatelets (GnP) at different concentrations. The films were fabricated by drop-casting and were hot-pressed at a temperature lower than their melting point to provide the molecular chains enough energy to reorientate while avoiding melting and degradation. It was found that hot-pressing increases crystallinity and improves mechanical properties. The Young’s modulus increased from 1.2 to 1.6 GPa for the poly(3-hydroxybutyrate) (P(3HB)) films and from 0.5 to 2.2 GPa for the 15 wt % P(3HB)/GnP composites. Electrical resistivity decreases enormously with GnP concentration and hot-pressing, reaching 6 Ω sq–1 for the hot-pressed 30 wt % P(3HB)/GnP composite. Finally, the hot-pressed P(3HB) samples exhibit remarkable oxygen barrier properties, with oxygen permeability reaching 2800 mL μm m–2 day–1, which becomes 895 mL μm m–2 day–1 when 15% GnP is added to the biopolymer matrix, one of the lowest values known for biopolymers and biocomposites. We propose that these biocomposites are used for elastic packaging and electronics

Roles of Education and IQ in Cognitive Reserve in Parkinson's Disease-Mild Cognitive Impairment.

Background/aimsThe role of cognitive reserve in Parkinson's disease (PD)-mild cognitive impairment (MCI) is incompletely understood.MethodsThe relationships between PD-MCI, years of education, and estimated premorbid IQ were examined in 119 consecutive non-demented PD patients using logistic regression models.ResultsHigher education and IQ were associated with reduced odds of PD-MCI in univariate analysis. In multivariable analysis, a higher IQ was associated with a significantly decreased odds of PD-MCI, but education was not.ConclusionThe association of higher IQ and decreased odds of PD-MCI supports a role for cognitive reserve in PD, but further studies are needed to clarify the interaction of IQ and education and the impact of other contributors such as employment and hobbies

Prevention and modulation of aminoglycoside ototoxicity (Review)

More than 60 years after their isolation and characterization, aminoglycoside (AG) antibiotics remain powerful agents in the treatment of severe gram-negative, enterococcal or mycobacterial infections. However, the clinical use of AGs is hampered by nephrotoxicity and ototoxicity, which often develop as a consequence of prolonged courses of therapy, or of administration of increased doses of these drugs. The discovery of non-ototoxic antibacterial agents, showing a wider spectrum of activity, has gradually decreased the use of AGs as first line antibiotics for many systemic infections. However, AGs are now undergoing an unexpected revival, being increasingly indicated for the treatment of severe emerging infections caused by organisms showing resistance to most first-line agents (e.g., multidrug-resistant tuberculosis, complicated nosocomially-acquired acute urinary tract infections). Increasing adoption of aminoglycosides poses again to scientists and physicians the problem of toxicity directed to the kidneys and to the inner ear. In particular, aminoglycoside-induced deafness can be profound and irreversible, especially in genetically predisposed patients. For this reason, an impressive amount of molecular strategies have been developed in the last decade to counteract the ototoxic effect of aminoglycosides. The present article overviews: i) the molecular mechanisms by which aminoglycosides exert their bactericidal activity, ii) the mechanisms whereby AGs exert their ototoxic activity in genetically-predisposed patients, iii) the drugs and compounds that have so far proven to prevent or modulate AG ototoxicity at the preclinical and/or clinical level, and iv) the dosage regimens that have so far been suggested to decrease the incidence of episodes of AG-induced ototoxicity

Extremely large extinction efficiency and field enhancement in terahertz resonant dipole nanoantennas

The distinctive ability of nanometallic structures to manipulate light at the nanoscale has recently promoted their use for a spectacular set of applications in a wide range of areas of research including artificial optical materials, nano-imaging, biosensing, and nonlinear optics. Here we transfer this concept to the terahertz spectral region, demonstrating a metal nanostructure in shape of a dipole nanoantenna, which can efficiently resonate at terahertz frequencies, showing an effective cross section >100 times larger than its geometrical area, and a field enhancement factor of ~280, confined on a lateral section of ~λ/1,000. These results lead to immediate applications in terahertz artificial materials exhibiting giant dichroism, suggest the use of dipole nanoantennas in nanostructure-based terahertz metamaterials, and pave the way for nanoantenna-enhanced terahertz few-molecule spectroscopy and localized terahertz nonlinear optics

Leveraging Google's Tensor Processing Units for tsunami-risk mitigation planning in the Pacific Northwest and beyond

Tsunami-risk mitigation planning has particular importance for communities like those of the Pacific Northwest, where coastlines are extremely dynamic and a seismically active subduction zone looms large. The challenge does not stop here for risk managers: mitigation options have multiplied since communities have realized the viability and benefits of nature-based solutions. To identify suitable mitigation options for their community, risk managers need the ability to rapidly evaluate several different options through fast and accessible tsunami models, but they may lack high-performance computing infrastructure. The goal of this work is to leverage Google's Tensor Processing Unit (TPU), a high-performance hardware device accessible via the Google Cloud framework, to enable the rapid evaluation of different tsunami-risk mitigation strategies available to all communities. We establish a starting point through a numerical solver of the nonlinear shallow-water equations that uses a fifth-order weighted essentially non-oscillatory method with the Lax–Friedrichs flux splitting and a total variation diminishing third-order Runge–Kutta method for time discretization. We verify numerical solutions through several analytical solutions and benchmarks, reproduce several findings about one particular tsunami-risk mitigation strategy, and model tsunami runup at Crescent City, California whose topography comes from a high-resolution digital elevation model. The direct measurements of the simulation's performance, energy usage, and ease of execution show that our code could be a first step towards a community-based, user-friendly virtual laboratory that can be run by a minimally trained user on the cloud thanks to the ease of use of the Google Cloud platform.</p

Permanent Lattice Compression of Lead-Halide Perovskite for Persistently Enhanced Optoelectronic Properties

Under mild mechanical pressure, halide perovskites show enhanced optoelectronic properties. However, these improvements are reversible upon decompression, and permanent enhancements have yet to be ..