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

ForestHash: Semantic Hashing With Shallow Random Forests and Tiny Convolutional Networks

Hash codes are efficient data representations for coping with the ever growing amounts of data. In this paper, we introduce a random forest semantic hashing scheme that embeds tiny convolutional neural networks (CNN) into shallow random forests, with near-optimal information-theoretic code aggregation among trees. We start with a simple hashing scheme, where random trees in a forest act as hashing functions by setting `1' for the visited tree leaf, and `0' for the rest. We show that traditional random forests fail to generate hashes that preserve the underlying similarity between the trees, rendering the random forests approach to hashing challenging. To address this, we propose to first randomly group arriving classes at each tree split node into two groups, obtaining a significantly simplified two-class classification problem, which can be handled using a light-weight CNN weak learner. Such random class grouping scheme enables code uniqueness by enforcing each class to share its code with different classes in different trees. A non-conventional low-rank loss is further adopted for the CNN weak learners to encourage code consistency by minimizing intra-class variations and maximizing inter-class distance for the two random class groups. Finally, we introduce an information-theoretic approach for aggregating codes of individual trees into a single hash code, producing a near-optimal unique hash for each class. The proposed approach significantly outperforms state-of-the-art hashing methods for image retrieval tasks on large-scale public datasets, while performing at the level of other state-of-the-art image classification techniques while utilizing a more compact and efficient scalable representation. This work proposes a principled and robust procedure to train and deploy in parallel an ensemble of light-weight CNNs, instead of simply going deeper.Comment: Accepted to ECCV 201

Development of specific PCR assays for the detection of Cryptocaryon irritans

Cryptocaryon irritans is one of the most important protozoan pathogens of marine fish, causing the “white spot” disease and posing a significant problem to marine aquaculture. In the present study, a C. irritans-specific reverse primer (S15) was designed based on the published sequence of the second internal transcribed spacer (ITS-2) of ribosomal DNA (rDNA) of C. irritans and used together with the conserved forward primer P1 to develop a specific polymerase chain reaction (PCR) assay for direct, rapid, and specific detection of C. irritans. The specificity of these primers was tested with both closely and distantly related ciliates (Pseudokeroronpsis rubra, Pseudokeroronpsis carnae, Euplotes sp. 1, Ichthyophthirius multifiliis, Pseudourostyla cristata, and Paramecium caudaium), and only C. irritans was detected and no product was amplified from any other ciliates examined in this study using the specific primer set P1-S15. The specific PCR assay was able to detect as low as 45 pg of C. irritans DNA and a nested PCR assay using two primer sets (P1/NC2, P1/S15) increased the sensitivity, allowing the detection of a single C. irritans. The species-specific PCR assays should provide useful tools for the diagnosis, prevention, and molecular epidemiological investigations of C. irritans infection in marine fish

Simultaneous determination of natural and synthetic steroid estrogens and their conjugates in aqueous matrices by liquid chromatography / mass spectrometry

An analytical method for the simultaneous determination of nine free and conjugated steroid estrogens was developed with application to environmental aqueous matrices. Solid phase extraction (SPE) was employed for isolation and concentration, with detection by liquid chromatography/mass spectrometry (LC/MS) using electrospray ionisation (ESI) in the negative mode. Method recoveries for various aqueous matrices (wastewater, lake and drinking water) were determined, recoveries proving to be sample dependent. When spiked at 50 ng/l concentrations in sewage influent, recoveries ranged from 62-89 % with relative standard deviations (RSD) < 8.1 %. In comparison, drinking water spiked at the same concentrations had recoveries between 82-100 % with an RSD < 5%. Ion suppression is a known phenomenon when using ESI; hence its impact on method recovery was elucidated for raw sewage. Both ion suppression from matrix interferences and the extraction procedure has bearing on the overall method recovery. Analysis of municipal raw sewage identified several of the analytes of interest at ng/l concentrations, estriol (E3) being the most abundant. Only one conjugate, estrone 3-sulphate (E1-3S) was observe

Measurements of the transverse-momentum-dependent cross sections of J /ψ production at mid-rapidity in proton+proton collisions at s =510 and 500 GeV with the STAR detector

We present measurements of the differential cross sections of inclusive J/ψ meson production as a function of transverse momentum (pTJ/ψ) using the μ+μ- and e+e- decay channels in proton+proton collisions at center-of-mass energies of 510 and 500 GeV, respectively, recorded by the STAR detector at the Relativistic Heavy Ion Collider. The measurement from the μ+μ- channel is for

Charge-dependent pair correlations relative to a third particle in p + Au and d + Au collisions at RHIC

Quark interactions with topological gluon configurations can induce chirality imbalance and local parity violation in quantum chromodynamics. This can lead to electric charge separation along the strong magnetic field in relativistic heavy-ion collisions – the chiral magnetic effect (CME). We report measurements by the STAR collaboration of a CME-sensitive observable in p+Au and d+Au collisions at 200 GeV, where the CME is not expected, using charge-dependent pair correlations relative to a third particle. We observe strong charge-dependent correlations similar to those measured in heavy-ion collisions. This bears important implications for the interpretation of the heavy-ion data

Measurement of inclusive J/ψ suppression in Au+Au collisions at sNN=200 GeV through the dimuon channel at STAR

J/ψ suppression has long been considered a sensitive signature of the formation of the Quark-Gluon Plasma (QGP) in relativistic heavy-ion collisions. In this letter, we present the first measurement of inclusive J/ψ production at mid-rapidity through the dimuon decay channel in Au+Au collisions at sNN=200 GeV with the STAR experiment. These measurements became possible after the installation of the Muon Telescope Detector was completed in 2014. The J/ψ yields are measured in a wide transverse momentum (pT) range of 0.15 GeV/c to 12 GeV/c from central to peripheral collisions. They extend the kinematic reach of previous measurements at RHIC with improved precision. In the 0-10% most central collisions, the J/ψ yield is suppressed by a factor of approximately 3 for pT&gt;5 GeV/c relative to that in p+p collisions scaled by the number of binary nucleon-nucleon collisions. The J/ψ nuclear modification factor displays little dependence on pT in all centrality bins. Model calculations can qualitatively describe the data, providing further evidence for the color-screening effect experienced by J/ψ mesons in the QGP

Observation of Excess J/ψ Yield at Very Low Transverse Momenta in Au+Au Collisions at sqrt[s_{NN}]=200 GeV and U+U Collisions at sqrt[s_{NN}]=193 GeV.

We report on the first measurements of J/ψ production at very low transverse momentum (p_{T}&lt;0.2  GeV/c) in hadronic Au+Au collisions at sqrt[s_{NN}]=200  GeV and U+U collisions at sqrt[s_{NN}]=193  GeV. Remarkably, the inferred nuclear modification factor of J/ψ at midrapidity in Au+Au (U+U) collisions reaches about 24 (52) for p_{T}&lt;0.05  GeV/c in the 60%-80% collision centrality class. This noteworthy enhancement cannot be explained by hadronic production accompanied by cold and hot medium effects. In addition, the dN/dt distribution of J/ψ for the very low p_{T} range is presented for the first time. The distribution is consistent with that expected from the Au nucleus and shows a hint of interference. Comparison of the measurements to theoretical calculations of coherent production shows that the excess yield can be described reasonably well and reveals a partial disruption of coherent production in semicentral collisions, perhaps due to the violent hadronic interactions. Incorporating theoretical calculations, the results strongly suggest that the dramatic enhancement of J/ψ yield observed at extremely low p_{T} originates from coherent photon-nucleus interactions. In particular, coherently produced J/ψ's in violent hadronic collisions may provide a novel probe of the quark-gluon plasma

Species-level functional profiling of metagenomes and metatranscriptomes.

Functional profiles of microbial communities are typically generated using comprehensive metagenomic or metatranscriptomic sequence read searches, which are time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed HUMAnN2, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community's known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is faster and produces more accurate gene family profiles. We applied HUMAnN2 to study clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species' genomic versus transcriptional contributions, and strain profiling. Further, we introduce 'contributional diversity' to explain patterns of ecological assembly across different microbial community types