Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs

In this work we propose a structured prediction technique that combines the virtues of Gaussian Conditional Random Fields (G-CRF) with Deep Learning: (a) our structured prediction task has a unique global optimum that is obtained exactly from the solution of a linear system (b) the gradients of our model parameters are analytically computed using closed form expressions, in contrast to the memory-demanding contemporary deep structured prediction approaches that rely on back-propagation-through-time, (c) our pairwise terms do not have to be simple hand-crafted expressions, as in the line of works building on the DenseCRF, but can rather be `discovered' from data through deep architectures, and (d) out system can trained in an end-to-end manner. Building on standard tools from numerical analysis we develop very efficient algorithms for inference and learning, as well as a customized technique adapted to the semantic segmentation task. This efficiency allows us to explore more sophisticated architectures for structured prediction in deep learning: we introduce multi-resolution architectures to couple information across scales in a joint optimization framework, yielding systematic improvements. We demonstrate the utility of our approach on the challenging VOC PASCAL 2012 image segmentation benchmark, showing substantial improvements over strong baselines. We make all of our code and experiments available at {https://github.com/siddharthachandra/gcrf}Comment: Our code is available at https://github.com/siddharthachandra/gcr

High-Affinity Quasi-Specific Sites in the Genome: How the DNA-Binding Proteins Cope with Them

AbstractMany prokaryotic transcription factors home in on one or a few target sites in the presence of a huge number of nonspecific sites. Our analysis of λ-repressor in the Escherichia coli genome based on single basepair substitution experiments shows the presence of hundreds of sites having binding energy within 3 Kcal/mole of the OR1 binding energy, and thousands of sites with binding energy above the nonspecific binding energy. The effect of such sites on DNA-based processes has not been fully explored. The presence of such sites dramatically lowers the occupation probability of the specific site far more than if the genome were composed of nonspecific sites only. Our Brownian dynamics studies show that the presence of quasi-specific sites results in very significant kinetic effects as well. In contrast to λ-repressor, the E. coli genome has orders of magnitude lower quasi-specific sites for GalR, an integral transcription factor, thus causing little competition for the specific site. We propose that GalR and perhaps repressors of the same family have evolved binding modes that lead to much smaller numbers of quasi-specific sites to remove the untoward effects of genomic DNA

Amino acid changes in the repressor of bacteriophage lambda due to temperature-sensitive mutations in its cI gene and the structure of a highly temperature-sensitive mutant repressor

The mutant cIts genes from seven different λcIts phages carrying tsU50, tsU9, tsU46, ts1, tsU51, tsI-22 and ts2 mutations were cloned in plasmid. The positions of these mutations and the resulting changes of amino acids in the repressor were determined by DNA sequencing. The first four mutations mapping in the N-terminal domain show the following changes: I21S, G53S, A62T and V73A, respectively. Of the three remaining mutations mapping in the C-terminal domain, cItsI-22 and cIts2 show N207T and K224E substitutions respectively, while the mutant cItsU51 gene carries F141I and P153L substitutions. Among these ts repressors, CIts2 having the charge-reversal change K224E was overexpressed from tac promoter in a plasmid and purified, and its structure and function were studied. Operator-binding studies suggest that the ts2 repressor is somewhat defective in monomer-dimer equilibrium and/ or cooperativity even at permissive temperatures and loses its operator-binding ability very rapidly above 25°C. Comparative studies of fluorescence and CD spectra, sulfhydryl group reactivity and elution behaviour in size-exclusion HPLC of both wild-type and ts2-mutant repressors at permissive and non-permissive temperatures suggest that the C-terminal domain of the ts2 repressor carrying a K224E substitution has a structure that does not favor tetramer formation at non-permissive temperatures

Coarse-to-Fine Annotation Enrichment for Semantic Segmentation Learning

Rich high-quality annotated data is critical for semantic segmentation learning, yet acquiring dense and pixel-wise ground-truth is both labor- and time-consuming. Coarse annotations (e.g., scribbles, coarse polygons) offer an economical alternative, with which training phase could hardly generate satisfactory performance unfortunately. In order to generate high-quality annotated data with a low time cost for accurate segmentation, in this paper, we propose a novel annotation enrichment strategy, which expands existing coarse annotations of training data to a finer scale. Extensive experiments on the Cityscapes and PASCAL VOC 2012 benchmarks have shown that the neural networks trained with the enriched annotations from our framework yield a significant improvement over that trained with the original coarse labels. It is highly competitive to the performance obtained by using human annotated dense annotations. The proposed method also outperforms among other state-of-the-art weakly-supervised segmentation methods.Comment: CIKM 2018 International Conference on Information and Knowledge Managemen

LISA as a dark energy probe

Recently it was shown that the inclusion of higher signal harmonics in the inspiral signals of binary supermassive black holes (SMBH) leads to dramatic improvements in parameter estimation with the Laser Interferometer Space Antenna (LISA). In particular, the angular resolution becomes good enough to identify the host galaxy or galaxy cluster, in which case the redshift can be determined by electromagnetic means. The gravitational wave signal also provides the luminosity distance with high accuracy, and the relationship between this and the redshift depends sensitively on the cosmological parameters, such as the equation-of-state parameter $w=p_{\rm DE}/\rho_{\rm DE}$ of dark energy. With a single binary SMBH event at $z < 1$ having appropriate masses and orientation, one would be able to constrain $w$ to within a few percent. We show that, if the measured sky location is folded into the error analysis, the uncertainty on $w$ goes down by an additional factor of 2-3, leaving weak lensing as the only limiting factor in using LISA as a dark energy probe.Comment: 11pages, 1 Table, minor changes in text, accepted for publication in Classical and Quantum Gravity (special issue for proceedings of 7th LISA symposium

Biocontrol of larval mosquitoes by Acilius sulcatus (Coleoptera: Dytiscidae)

<p>Abstract</p> <p>Background</p> <p>Problems associated with resistant mosquitoes and the effects on non-target species by chemicals, evoke a reason to find alternative methods to control mosquitoes, like the use of natural predators. In this regard, aquatic coleopterans have been explored less compared to other insect predators. In the present study, an evaluation of the role of the larvae of <it>Acilius sulcatus </it>Linnaeus 1758 (Coleoptera: Dytiscidae) as predator of mosquito immatures was made in the laboratory. Its efficacy under field condition was also determined to emphasize its potential as bio-control agent of mosquitoes.</p> <p>Methods</p> <p>In the laboratory, the predation potential of the larvae of <it>A. sulcatus </it>was assessed using the larvae of <it>Culex quinquefasciatus </it>Say 1823 (Diptera: Culicidae) as prey at varying predator and prey densities and available space. Under field conditions, the effectiveness of the larvae of <it>A. sulcatus </it>was evaluated through augmentative release in ten cemented tanks hosting immatures of different mosquito species at varying density. The dip density changes in the mosquito immatures were used as indicator for the effectiveness of <it>A. sulcatus </it>larvae.</p> <p>Results</p> <p>A single larva of <it>A. sulcatus </it>consumed on an average 34 IV instar larvae of <it>Cx. quinquefasciatus </it>in a 24 h period. It was observed that feeding rate of <it>A. sulcatus </it>did not differ between the light-on (6 a.m. – 6 p.m.), and dark (6 p.m. – 6 a.m.) phases, but decreased with the volume of water i.e., space availability. The prey consumption of the larvae of <it>A. sulcatus </it>differed significantly (P < 0.05) with different prey, predator and volume combinations, revealed through univariate ANOVA. The field study revealed a significant decrease (p < 0.05) in larval density of different species of mosquitoes after 30 days from the introduction of <it>A. sulcatus </it>larvae, while with the withdrawal, a significant increase (p < 0.05) in larval density was noted indicating the efficacy of <it>A. sulcatus </it>in regulating mosquito immatures. In the control tanks, mean larval density did not differ (p > 0.05) throughout the study period.</p> <p>Conclusion</p> <p>the larvae of the dytiscid beetle <it>A. sulcatus </it>proved to be an efficient predator of mosquito immatures and may be useful in biocontrol of medically important mosquitoes.</p

Overexpression of Prothymosin Alpha Predicts Poor Disease Outcome in Head and Neck Cancer

In our recent study, tissue proteomic analysis of oral pre-malignant lesions (OPLs) and normal oral mucosa led to the identification of a panel of biomarkers, including prothymosin alpha (PTMA), to distinguish OPLs from histologically normal oral tissues. This study aimed to determine the clinical significance of PTMA overexpression in oral squamous cell hyperplasia, dysplasia and head and neck squamous cell carcinoma (HNSCC).Immunohistochemistry of PTMA protein was performed in HNSCCs (n = 100), squamous cell hyperplasia (n = 116), dysplasia (n = 50) and histologically normal oral tissues (n = 100). Statistical analysis was carried out to determine the association of PTMA overexpression with clinicopathological parameters and disease prognosis over 7 years for HNSCC patients.<0.001). Chi-square analysis showed significant association of nuclear PTMA with advanced tumor stages (III+IV). Kaplan Meier survival analysis indicated reduced disease free survival (DFS) in HNSCC patients (p<0.001; median survival 11 months). Notably, Cox-multivariate analysis revealed nuclear PTMA as an independent predictor of poor prognosis of HNSCC patients (p<0.001, Hazard's ratio, HR = 5.2, 95% CI = 2.3–11.8) in comparison with the histological grade, T-stage, nodal status and tumor stage.Nuclear PTMA may serve as prognostic marker in HNSCC to determine the subset of patients that are likely to show recurrence of the disease