Indian Institute of Technology Bombay

About: Indian Institute of Technology Bombay is a education organization based out in Mumbai, India. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 16756 authors who have published 33588 publications receiving 570559 citations.

Cracking in drying colloidal films.

Abstract: It has long been known that thick films of colloidal dispersions such as wet clays, paints, and coatings crack under drying. Although capillary stresses generated during drying have been recently identified as the cause for cracking, the existence of a maximum crack-free film thickness that depends on particle size, rigidity, and packing has not been understood. Here, we identify two distinct regimes for crack-free films based on the magnitude of compressive strain at the maximum attainable capillary pressure and show remarkable agreement of measurements with our theory. We anticipate our results to not only form the basis for design of coating formulations for the paints, coatings, and ceramics industry but also assist in the production of crack-free photonic band gap crystals.

Technical design report for the upgrade of the ALICE inner tracking system

Abstract: ALICE (A Large Ion Collider Experiment) is studying the physics of strongly interacting matter, and in particular the properties of the Quark–Gluon Plasma (QGP), using proton–proton, proton–nucleus and nucleus–nucleus collisions at the CERN LHC (Large Hadron Collider). The ALICE Collaboration is preparing a major upgrade of the experimental apparatus, planned for installation in the second long LHC shutdown in the years 2018–2019. A key element of the ALICE upgrade is the construction of a new, ultra-light, high- resolution Inner Tracking System (ITS) based on monolithic CMOS pixel detectors. The primary focus of the ITS upgrade is on improving the performance for detection of heavy-flavour hadrons, and of thermal photons and low-mass di- electrons emitted by the QGP. With respect to the current detector, the new Inner Tracking System will significantly enhance the determination of the distance of closest approach to the primary vertex, the tracking efficiency at low transverse momenta, and the read-out rate capabilities. This will be obtained by seven concentric detector layers based on a 50 μm thick CMOS pixel sensor with a pixel pitch of about 30×30 μm2. This document, submitted to the LHCC (LHC experiments Committee) in September 2013, presents the design goals, a summary of the R&D activities, with focus on the technical implementation of the main detector components, and the projected detector and physics performance.

A Multi-Organ Nucleus Segmentation Challenge

Abstract: Generalized nucleus segmentation techniques can contribute greatly to reducing the time to develop and validate visual biomarkers for new digital pathology datasets. We summarize the results of MoNuSeg 2018 Challenge whose objective was to develop generalizable nuclei segmentation techniques in digital pathology. The challenge was an official satellite event of the MICCAI 2018 conference in which 32 teams with more than 80 participants from geographically diverse institutes participated. Contestants were given a training set with 30 images from seven organs with annotations of 21,623 individual nuclei. A test dataset with 14 images taken from seven organs, including two organs that did not appear in the training set was released without annotations. Entries were evaluated based on average aggregated Jaccard index (AJI) on the test set to prioritize accurate instance segmentation as opposed to mere semantic segmentation. More than half the teams that completed the challenge outperformed a previous baseline. Among the trends observed that contributed to increased accuracy were the use of color normalization as well as heavy data augmentation. Additionally, fully convolutional networks inspired by variants of U-Net, FCN, and Mask-RCNN were popularly used, typically based on ResNet or VGG base architectures. Watershed segmentation on predicted semantic segmentation maps was a popular post-processing strategy. Several of the top techniques compared favorably to an individual human annotator and can be used with confidence for nuclear morphometrics.