Learning to Hash-tag Videos with Tag2Vec

User-given tags or labels are valuable resources for semantic understanding of visual media such as images and videos. Recently, a new type of labeling mechanism known as hash-tags have become increasingly popular on social media sites. In this paper, we study the problem of generating relevant and useful hash-tags for short video clips. Traditional data-driven approaches for tag enrichment and recommendation use direct visual similarity for label transfer and propagation. We attempt to learn a direct low-cost mapping from video to hash-tags using a two step training process. We first employ a natural language processing (NLP) technique, skip-gram models with neural network training to learn a low-dimensional vector representation of hash-tags (Tag2Vec) using a corpus of 10 million hash-tags. We then train an embedding function to map video features to the low-dimensional Tag2vec space. We learn this embedding for 29 categories of short video clips with hash-tags. A query video without any tag-information can then be directly mapped to the vector space of tags using the learned embedding and relevant tags can be found by performing a simple nearest-neighbor retrieval in the Tag2Vec space. We validate the relevance of the tags suggested by our system qualitatively and quantitatively with a user study

Antidiabetic activities of Cassia occidentalis

The present investigation was carried out to evaluate the anti-diabetic activities of Cassia occidentalis (Seena, coffee weed), a well known medicinal plant commonly found in India and other tropical countries. Various medicinal properties have been attributed to this plant in the traditional system of Indian medicine. The aqueous and methanolic extracts of aerial parts, viz. leaves, stem and seeds of the plant, Cassia occidentalis possessed anti-hyperglycemic/ anti-diabetic activity against alloxan-induced animal model. All aqueous-treated rats showed no discernible behavioral changes up to 3000 mg/kg by oral route. No mortality was observed at this dose during 72 h observation period. Amongst all the extracts, potent anti-diabetic activity was observed in aqueous extracts of leaves of C. occidentalis followed by aqueous extracts of seeds and aqueous extracts of stem. In normal animals, significant (p<0.05) reduction in the blood glucose level was observed by the aqueous extracts as compared to the control and methanolic extracts. However, treatment of methanolic extracts of aerial parts of C. occidentalis could not bring back the sugar to normal levels. Acute and chronic treatment of the aqueous extract of aerial parts of C. occidentalis (3000 mg/kg) in alloxan-induced diabetic rats resulted in a significant (p<0.05) decrease in the elevated blood glucose levels as compared to the control, there was significant reduction in blood glucose level in the group treated with glibenclamide at 0.5 mg/kg. The results showed that blood glucose level gets decreased after varying the dose level. Thus the findings confirmed that level of blood glucose gets normal in dose-dependent manner

Interactive Segmentation of Radiance Fields

Radiance Fields (RF) are popular to represent casually-captured scenes for new view generation and have been used for applications beyond it. Understanding and manipulating scenes represented as RFs have to naturally follow to facilitate mixed reality on personal spaces. Semantic segmentation of objects in the 3D scene is an important step for that. Prior segmentation efforts using feature distillation show promise but don't scale to complex objects with diverse appearance. We present a framework to interactively segment objects with fine structure. Nearest neighbor feature matching identifies high-confidence regions of the objects using distilled features. Bilateral filtering in a joint spatio-semantic space grows the region to recover accurate segmentation. We show state-of-the-art results of segmenting objects from RFs and compositing them to another scene, changing appearance, etc., moving closer to rich scene manipulation and understanding. Project Page: https://rahul-goel.github.io/isrf/Comment: Project Page: https://rahul-goel.github.io/isrf

Molecular Analysis of a Leprosy Immunotherapeutic Bacillus Provides Insights into Mycobacterium Evolution

BACKGROUND: Evolutionary dynamics plays a central role in facilitating the mechanisms of species divergence among pathogenic and saprophytic mycobacteria. The ability of mycobacteria to colonize hosts, to proliferate and to cause diseases has evolved due to its predisposition to various evolutionary forces acting over a period of time. Mycobacterium indicus pranii (MIP), a taxonomically unknown 'generalist' mycobacterium, acts as an immunotherapeutic against leprosy and is approved for use as a vaccine against it. The large-scale field trials of this MIP based leprosy vaccine coupled with its demonstrated immunomodulatory and adjuvant property has led to human clinical evaluations of MIP in interventions against HIV-AIDS, psoriasis and bladder cancer. MIP, commercially available as 'Immuvac', is currently the focus of advanced phase III clinical trials for its antituberculosis efficacy. Thus a comprehensive analysis of MIP vis-à-vis evolutionary path, underpinning its immanent immunomodulating properties is of the highest desiderata. PRINCIPAL FINDINGS: Genome wide comparisons together with molecular phylogenetic analyses by fluorescent amplified fragment length polymorphism (FAFLP), enterobacterial repetitive intergenic consensus (ERIC) based genotyping and candidate orthologues sequencing revealed that MIP has been the predecessor of highly pathogenic Mycobacterium avium intracellulare complex (MAIC) that did not resort to parasitic adaptation by reductional gene evolution and therefore, preferred a free living life-style. Further analysis suggested a shared aquatic phase of MAIC bacilli with the early pathogenic forms of Mycobacterium, well before the latter diverged as 'specialists'. CONCLUSIONS/SIGNIFICANCE: This evolutionary paradigm possibly affirms to marshall our understanding about the acquisition and optimization of virulence in mycobacteria and determinants of boundaries therein

Investigation of charge carrier dynamics in Ti3C2Tx MXene for ultrafast photonics applications

The rapid advancement of nanomaterials has paved the way for various technological breakthroughs, and MXenes, in particular, have gained substantial attention due to their unique properties such as high conductivity, broad-spectrum absorption strength, and tunable band gap. This article presents the impact of the process parameters on the structural and optical properties of Ti3C2Tx MXene for application in ultrafast dynamics. XRD along with Raman spectroscopy studies, confirmed the synthesis of a single phase from their MAX phase Ti3AlC2. The complete etching of Al and increase in the interplanar distance is also observed on centrifugation at very high speed. The ultrafast transient absorption spectroscopy used to understand the effect of centrifuge speed on the charge carrier dynamics and ultrafast spectrum of MXene displayed that the carrier lifetime is critically influenced by rotation per minute (rpm) e.g. faster decay lifetime at 10k rpm than 7k rpm. The electronic relaxation probed using the time-resolved photoluminescence (TRPL) technique exhibits an average decay time of 5.13 ns and 5.35 ns at the 7k and 10k rpm, respectively, which confirms that the optical properties of the MXene are strongly affected by the centrifuge speed. The synthesized MXene at 10k rpm typically suggests that radiative processes due to longer decay lifetime and experiences fewer nonradiative losses, resulting in enhanced luminescence properties.Comment: 21 pages , 6 figure

Polyphasic Taxonomic Analysis Establishes Mycobacterium indicus pranii as a Distinct Species

that integrate its phenotypic, chemotaxonomic and molecular phylogenetic attributes..

The 3-Point Method: A Fast, Accurate and Robust Solution to Vanishing Point Estimation

Vanishing points can provide information about the 3D world and hence are of great interest for machine vision applications. In this paper, we present a single point perspectivity based method for robust and accurate estimation of Vanishing Points (VPs). It utilizes location of 3 collinear points in image space and their distance ratio in the world frame for VP estimation. We present an algebraic derivation for the proposed 3-Point (3-P) method. It provides us a non-iterative, closed-form solution. The 3-P results are compared with ground truth of VP and it is shown to be accurate. Its robustness to point selection and image noise is proved through extensive simulations. Computational time requirement for 3-P method is shown to be much less than least squares based method. The 3-P method is extremely useful for accurate VP estimation in structured and well-defined environments