3D Depthwise Convolution: Reducing Model Parameters in 3D Vision Tasks

Standard 3D convolution operations require much larger amounts of memory and computation cost than 2D convolution operations. The fact has hindered the development of deep neural nets in many 3D vision tasks. In this paper, we investigate the possibility of applying depthwise separable convolutions in 3D scenario and introduce the use of 3D depthwise convolution. A 3D depthwise convolution splits a single standard 3D convolution into two separate steps, which would drastically reduce the number of parameters in 3D convolutions with more than one order of magnitude. We experiment with 3D depthwise convolution on popular CNN architectures and also compare it with a similar structure called pseudo-3D convolution. The results demonstrate that, with 3D depthwise convolutions, 3D vision tasks like classification and reconstruction can be carried out with more light-weighted neural networks while still delivering comparable performances.Comment: Work in progres

Effect of jet fuel aromatics on in-flame soot distribution and particle morphology in a small-bore compression ignition engine

This study reports the effect of fuel aromatic content on soot particle development inside the cylinder of an optically accessible engine. A custom-made set of fuels of 4%, 14% and 24% aromatic content was carefully studied under pilot-main injection conditions. Time-resolved imaging of cool frame, OH* chemiluminescence signals and soot luminosity were performed to visualise the overall reaction development. Planar laser induced fluorescence imaging of HCHO and incandescence imaging of soot were also performed to obtain detailed understanding of reactions and soot distributions. Soot is analysed at a particle level. Using the thermophoresis-based particle sampling method, soot aggregates were collected from multiple in-bowl locations. The subsequent transmission electron microscope (TEM) imaging of the collected soot particles enables structural analysis of soot particles as well as sub-nano-scale carbon layers. The results showed that the aromatic content has little impact on reactions and flame development among the tested fuels. However, the soot formation starts to occur earlier, and its growth rate is much higher for a higher aromatic fuel. As a result, both the peak soot and remaining soot is measured higher for a higher aromatic fuel. The carbon-layer fringe analysis shows more mature, graphitised structures with higher aromatics at both formation-dominant and oxidation-dominant stages. The most noticeable trend is observed from larger soot aggregates for a higher aromatic fuel while the overall shapes are similar

Quantifying drug-induced dyskinesias in the arms using digitised spiral-drawing tasks.

In this study, we quantify the severity of drug-induced dyskinesias in the arms of Parkinson's disease (PD) patients using digitised spiral-drawing tasks. Two spiral drawings, namely a circular and a square spiral, are designed to, respectively, represent the continuous and discrete arm motions, and the size of the spiral is decided so that both the distal and proximal arm joints are involved. Fifteen PD patients, average disease duration 14.4+/-7.4 years, were assessed 30 min after a levodopa challenge whilst performing circular and square spiral-drawing tasks. The velocity of drawing movements was computed and the amplitude of the involuntary dyskinetic movements was measured as the standard deviation of the drawing velocity (SD-DV). The mean amplitude of dyskinetic movements was compared between arms and tasks and was correlated with clinical measures including the Bain dyskinesia scale and the total unified Parkinson's disease rating scale (UPDRS) score. The results showed that there was no statistically significant difference in the amplitude of dyskinesias either between the arms or between the continuous (circular) and discrete (square) spiral drawings in this group of PD patients, but interestingly the interaction between arm and drawing pattern was significant. Significant correlations were found between the magnitude of dyskinesia measured from the spiral-drawing tasks and both the 'on' or 'off' UPDRS and also the Bain dyskinesia scale. We conclude that the drawing tasks may be used to provide an objective method of quantifying the severity of drug-induced dyskinesias in the arm in PD patients

Material-independent crack arrest statistics: Application to indentation experiments

An extensive experimental study of indentation and crack arrest statistics is presented for four different brittle materials (alumina, silicon carbide, silicon nitride, glass). Evidence is given that the crack length statistics can be described by a universal (i.e. material independent) distribution. The latter directly derives from results obtained when modeling crack propagation as a depinning phenomenon. Crack arrest (or effective toughness) statistics appears to be fully characterized by two parameters, namely, an asymptotic crack length (or macroscopic toughness) value and a power law size dependent width. The experimental knowledge of the crack arrest statistics at one given scale thus gives access to its knowledge at all scales

Counting, generating and sampling tree alignments

Pairwise ordered tree alignment are combinatorial objects that appear in RNA secondary structure comparison. However, the usual representation of tree alignments as supertrees is ambiguous, i.e. two distinct supertrees may induce identical sets of matches between identical pairs of trees. This ambiguity is uninformative, and detrimental to any probabilistic analysis.In this work, we consider tree alignments up to equivalence. Our first result is a precise asymptotic enumeration of tree alignments, obtained from a context-free grammar by mean of basic analytic combinatorics. Our second result focuses on alignments between two given ordered trees $S$ and $T$. By refining our grammar to align specific trees, we obtain a decomposition scheme for the space of alignments, and use it to design an efficient dynamic programming algorithm for sampling alignments under the Gibbs-Boltzmann probability distribution. This generalizes existing tree alignment algorithms, and opens the door for a probabilistic analysis of the space of suboptimal RNA secondary structures alignments.Comment: ALCOB - 3rd International Conference on Algorithms for Computational Biology - 2016, Jun 2016, Trujillo, Spain. 201

AA--Dependence of ΛΛ\Lambda\Lambda Bond Energies in Double---Λ\Lambda Hypernuclei

The $A$-dependence of the bond energy $\Delta B_{\Lambda\Lambda}$ of the ${\Lambda\Lambda}$ hypernuclear ground states is calculated in a three-body ${\Lambda + \Lambda + {^{A}Z}}$ model and in the Skyrme-Hartree-Fock approach. Various ${\Lambda\Lambda}$ and $\Lambda$-nucleus or ${\Lambda N}$ potentials are used and the sensitivity of $\Delta B_{\Lambda\Lambda}$ to the interactions is discussed. It is shown that in medium and heavy ${\Lambda\Lambda}$ hypernuclei, $\Delta B_{\Lambda\Lambda}$ is a linear function of $r_{\Lambda}^{-3}$, where $r_\Lambda$ is rms radius of the hyperon orbital. It looks unlikely that it will be possible to extract ${\Lambda\Lambda}$ interaction from the double-$\Lambda$ hypernuclear energies only, the additional information about the $\Lambda$-core interaction, in particular, on $r_{\Lambda}$ is needed.Comment: 11 pages, LaTex, 3 figure

Generalized Ricci Curvature Bounds for Three Dimensional Contact Subriemannian manifolds

Measure contraction property is one of the possible generalizations of Ricci curvature bound to more general metric measure spaces. In this paper, we discover sufficient conditions for a three dimensional contact subriemannian manifold to satisfy this property.Comment: 49 page

Learning Shape Priors for Single-View 3D Completion and Reconstruction

The problem of single-view 3D shape completion or reconstruction is challenging, because among the many possible shapes that explain an observation, most are implausible and do not correspond to natural objects. Recent research in the field has tackled this problem by exploiting the expressiveness of deep convolutional networks. In fact, there is another level of ambiguity that is often overlooked: among plausible shapes, there are still multiple shapes that fit the 2D image equally well; i.e., the ground truth shape is non-deterministic given a single-view input. Existing fully supervised approaches fail to address this issue, and often produce blurry mean shapes with smooth surfaces but no fine details. In this paper, we propose ShapeHD, pushing the limit of single-view shape completion and reconstruction by integrating deep generative models with adversarially learned shape priors. The learned priors serve as a regularizer, penalizing the model only if its output is unrealistic, not if it deviates from the ground truth. Our design thus overcomes both levels of ambiguity aforementioned. Experiments demonstrate that ShapeHD outperforms state of the art by a large margin in both shape completion and shape reconstruction on multiple real datasets.Comment: ECCV 2018. The first two authors contributed equally to this work. Project page: http://shapehd.csail.mit.edu

Exploration of a potent PI3 kinase/mTOR inhibitor as a novel anti-fibrotic agent in IPF

© 2016 BMJ Publishing Group Ltd & British Thoracic Society.Rationale Idiopathic pulmonary fibrosis (IPF) is the most rapidly progressive and fatal of all fibrotic conditions with no curative therapies. Common pathomechanisms between IPF and cancer are increasingly recognised, including dysfunctional pan-PI3 kinase (PI3K) signalling as a driver of aberrant proliferative responses. GSK2126458 is a novel, potent, PI3K/mammalian target of rapamycin (mTOR) inhibitor which has recently completed phase I trials in the oncology setting. Our aim was to establish a scientific and dosing framework for PI3K inhibition with this agent in IPF at a clinically developable dose. Methods We explored evidence for pathway signalling in IPF lung tissue and examined the potency of GSK2126458 in fibroblast functional assays and precision-cut IPF lung tissue. We further explored the potential of IPF patient-derived bronchoalveolar lavage (BAL) cells to serve as pharmacodynamic biosensors to monitor GSK2126458 target engagement within the lung. Results We provide evidence for PI3K pathway activation in fibrotic foci, the cardinal lesions in IPF. GSK2126458 inhibited PI3K signalling and functional responses in IPF-derived lung fibroblasts, inhibiting Akt phosphorylation in IPF lung tissue and BAL derived cells with comparable potency. Integration of these data with GSK2126458 pharmacokinetic data from clinical trials in cancer enabled modelling of an optimal dosing regimen for patients with IPF. Conclusions Our data define PI3K as a promising therapeutic target in IPF and provide a scientific and dosing framework for progressing GSK2126458 to clinical testing in this disease setting. A proof-ofmechanism trial of this agent is currently underway. Trial registration number NCT01725139, pre-clinical

Field-induced water electrolysis switches an oxide semiconductor from an insulator to a metal

Here we demonstrate that water-infiltrated nanoporous glass electrically switches an oxide semiconductor from an insulator to metal. We fabricated the field effect transistor structure on an oxide semiconductor, SrTiO3, using 100%-water-infiltrated nanoporous glass - amorphous 12CaO*7Al2O3 - as the gate insulator. For positive gate voltage, electron accumulation, water electrolysis and electrochemical reduction occur successively on the SrTiO3 surface at room temperature, leading to the formation of a thin (~3 nm) metal layer with an extremely high electron concentration of 10^15-10^16 cm^-2, which exhibits exotic thermoelectric behaviour.Comment: 21 pages, 12 figure