Showing papers by "Indian Institute of Science published in 2019"

China and India lead in greening of the world through land-use management

Abstract: Satellite data show increasing leaf area of vegetation due to direct (human land-use management) and indirect factors (climate change, CO2 fertilization, nitrogen deposition, recovery from natural disturbances, etc.). Among these, climate change and CO2 fertilization effect seem to be the dominant drivers. However, recent satellite data (2000-2017) reveal a greening pattern that is strikingly prominent in China and India, and overlapping with croplands world-wide. China alone accounts for 25% of the global net increase in leaf area with only 6.6% of global vegetated area. The greening in China is from forests (42%) and croplands (32%), but in India is mostly from croplands (82%) with minor contribution from forests (4.4%). China is engineering ambitious programs to conserve and expand forests with the goal of mitigating land degradation, air pollution and climate change. Food production in China and India has increased by over 35% since 2000 mostly due to increasing harvested area through multiple cropping facilitated by fertilizer use and surface/ground-water irrigation. Our results indicate that the direct factor is a key driver of the "Greening Earth", accounting for over a third, and likely more, of the observed net increase in green leaf area. They highlight the need for realistic representation of human land-use practices in Earth system models.

Covalent Organic Frameworks: Chemistry beyond the Structure.

Abstract: Covalent organic frameworks (COFs) represent a new field of rapidly growing chemical research that takes direct inspiration from diverse covalent bonds existing between atoms. The success of linking atoms in two and three dimensions to construct extended framework structures moved the chemistry of COFs beyond the structures to methodologies, highlighting the possibility of prospective applications. Although structure to property relation in COFs has led to fascinating properties, chemical stability, processability and scalability were some of the important challenges that needed to be overcome for their successful implementation. In this Perspective, we take a closer look at the growth of COFs from mere supramolecular structures to potential industrializable materials.

A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task

Abstract: Response inhibition is essential for navigating everyday life. Its derailment is considered integral to numerous neurological and psychiatric disorders, and more generally, to a wide range of behavioral and health problems. Response-inhibition efficiency furthermore correlates with treatment outcome in some of these conditions. The stop-signal task is an essential tool to determine how quickly response inhibition is implemented. Despite its apparent simplicity, there are many features (ranging from task design to data analysis) that vary across studies in ways that can easily compromise the validity of the obtained results. Our goal is to facilitate a more accurate use of the stop-signal task. To this end, we provide 12 easy-to-implement consensus recommendations and point out the problems that can arise when they are not followed. Furthermore, we provide user-friendly open-source resources intended to inform statistical-power considerations, facilitate the correct implementation of the task, and assist in proper data analysis.

Bounds on Slow Roll and the de Sitter Swampland

Abstract: The recently introduced swampland criterion for de Sitter [17] can be viewed as a (hierarchically large) bound on the smallness of the slow roll parameter 𝜖V. This leads us to consider the other slow roll parameter ηV more closely, and we are lead to conjecture that the bound is not necessarily on 𝜖V, but on slow roll itself. A natural refinement of the de Sitter swampland conjecture is therefore that slow roll is violated at $$ \mathcal{O} $$ (1) in Planck units in any UV complete theory. A corollary is that 𝜖V need not necesarily be $$ \mathcal{O} $$ (1), if $$ {\eta}_V\lesssim -\mathcal{O}(1) $$ holds. We consider various tachyonic tree level constructions of de Sitter in IIA/IIB string theory (as well as closely related models of inflation), which superficially violate [17], and show that they are consistent with this refined version of the bound. The phrasing in terms of slow roll makes it plausible why both versions of the conjecture run into trouble when the number of e-folds during inflation is high. We speculate that one way to evade the bound could be to have a large number of fields, like in N -flation.

Combined measurements of Higgs boson couplings in proton–proton collisions at √s=13Te

Abstract: Combined measurements of the production and decay rates of the Higgs boson, as well as its couplings to vector bosons and fermions, are presented. The analysis uses the LHC proton–proton collision data set recorded with the CMS detector in 2016 at $\sqrt{s}=13\,\text {Te}\text {V} $ , corresponding to an integrated luminosity of 35.9 ${\,\text {fb}^{-1}} $ . The combination is based on analyses targeting the five main Higgs boson production mechanisms (gluon fusion, vector boson fusion, and associated production with a $\mathrm {W}$ or $\mathrm {Z}$ boson, or a top quark-antiquark pair) and the following decay modes: $\mathrm {H} \rightarrow \gamma \gamma $ , $\mathrm {Z}\mathrm {Z}$ , $\mathrm {W}\mathrm {W}$ , $\mathrm {\tau }\mathrm {\tau }$ , $\mathrm {b} \mathrm {b} $ , and $\mathrm {\mu }\mathrm {\mu }$ . Searches for invisible Higgs boson decays are also considered. The best-fit ratio of the signal yield to the standard model expectation is measured to be $\mu =1.17\pm 0.10$ , assuming a Higgs boson mass of $125.09\,\text {Ge}\text {V} $ . Additional results are given for various assumptions on the scaling behavior of the production and decay modes, including generic parametrizations based on ratios of cross sections and branching fractions or couplings. The results are compatible with the standard model predictions in all parametrizations considered. In addition, constraints are placed on various two Higgs doublet models.

Definition of the chalcogen bond (IUPAC Recommendations 2019)

Abstract: This recommendation proposes a definition for the term ``chalcogen bond''; it is recommended the term is used to designate the specific subset of inter- and intramolecular interactions formed by chalcogen atoms wherein the Group 16 element is the electrophilic site.

Triazine Functionalized Porous Covalent Organic Framework for Photo-organocatalytic E–Z Isomerization of Olefins

Abstract: Visible light-mediated photocatalytic organic transformation has drawn significant attention as an alternative process for replacing thermal reactions. Although precious metal/organic dyes based homogeneous photocatalysts have been developed, their toxic and nonreusable nature makes them inappropriate for large-scale production. Therefore, we have synthesized a triazine and a keto functionalized nonmetal based covalent organic framework (TpTt) for heterogeneous photocatalysis. As the catalyst shows significant absorption of visible light, it has been applied for the photocatalytic uphill conversion of trans-stilbene to cis-stilbene in the presence of blue light-emitting diodes with broad substrate scope via an energy transfer process.

NHC-Catalyzed Generation of α,β-Unsaturated Acylazoliums for the Enantioselective Synthesis of Heterocycles and Carbocycles.

Abstract: ConspectusThis Account is aimed at highlighting the recent developments in the N-heterocyclic carbene (NHC)-catalyzed generation of α,β-unsaturated acylazolium intermediates and their subsequent reactivity with (bis)nucleophiles thereby shedding light on the power of this NHC-bound intermediate in organocatalysis. This key intermediate can be generated by the addition of NHCs to α,β-unsaturated aldehyde or acid derivatives. A wide variety of bisnucleophiles can add across the α,β-unsaturated acylazoliums to form various five and six-membered heterocycles and carbocycles. Moreover, suitably substituted nucleophiles can add to this intermediate and result in valuable products following cascade processes. Employing chiral NHCs in the process can result in the enantioselective synthesis of valuable compounds.In 2013, we developed a unified strategy for the enantioselective synthesis of dihydropyranones and dihydropyridinones by the NHC-catalyzed formal [3 + 3] annulation of 2-bromoenals with readily available...

Machine Learning in the Air

Abstract: Thanks to the recent advances in processing speed, data acquisition and storage, machine learning (ML) is penetrating every facet of our lives, and transforming research in many areas in a fundamental manner. Wireless communications is another success story – ubiquitous in our lives, from handheld devices to wearables, smart homes, and automobiles. While recent years have seen a flurry of research activity in exploiting ML tools for various wireless communication problems, the impact of these techniques in practical communication systems and standards is yet to be seen. In this paper, we review some of the major promises and challenges of ML in wireless communication systems, focusing mainly on the physical layer. We present some of the most striking recent accomplishments that ML techniques have achieved with respect to classical approaches, and point to promising research directions where ML is likely to make the biggest impact in the near future. We also highlight the complementary problem of designing physical layer techniques to enable distributed ML at the wireless network edge, which further emphasizes the need to understand and connect ML with fundamental concepts in wireless communications.

Cavity Catalysis by Cooperative Vibrational Strong Coupling of Reactant and Solvent Molecules.

Abstract: Here, we report the catalytic effect of vibrational strong coupling (VSC) on the solvolysis of para-nitrophenyl acetate (PNPA), which increases the reaction rate by an order of magnitude. This is observed when the microfluidic Fabry-Perot cavity in which the VSC is generated is tuned to the C=O vibrational stretching mode of both the reactant and solvent molecules. Thermodynamic experiments confirm the catalytic nature of VSC in the system. The change in the reaction rate follows an exponential relation with respect to the coupling strength of the solvent, indicating a cooperative effect between the solvent molecules and the reactant. Furthermore, the study of the solvent kinetic isotope effect clearly shows that the vibrational overlap of the C=O vibrational bands of the reactant and the strongly coupled solvent molecules is critical for the catalysis in this reaction. The combination of cooperative effects and cavity catalysis confirms the potential of VSC as a new frontier in chemistry.

Structural insights into the activation of metabotropic glutamate receptors.

Abstract: Metabotropic glutamate receptors are family C G-protein-coupled receptors. They form obligate dimers and possess extracellular ligand-binding Venus flytrap domains, which are linked by cysteine-rich domains to their 7-transmembrane domains. Spectroscopic studies show that signalling is a dynamic process, in which large-scale conformational changes underlie the transmission of signals from the extracellular Venus flytraps to the G protein-coupling domains-the 7-transmembrane domains-in the membrane. Here, using a combination of X-ray crystallography, cryo-electron microscopy and signalling studies, we present a structural framework for the activation mechanism of metabotropic glutamate receptor subtype 5. Our results show that agonist binding at the Venus flytraps leads to a compaction of the intersubunit dimer interface, thereby bringing the cysteine-rich domains into close proximity. Interactions between the cysteine-rich domains and the second extracellular loops of the receptor enable the rigid-body repositioning of the 7-transmembrane domains, which come into contact with each other to initiate signalling.

New topological invariants in non-Hermitian systems.

Abstract: Both theoretical and experimental studies of topological phases in non-Hermitian systems have made a remarkable progress in the last few years of research. In this article, we review the key concepts pertaining to topological phases in non-Hermitian Hamiltonians with relevant examples and realistic model setups. Discussions are devoted to both the adaptations of topological invariants from Hermitian to non-Hermitian systems, as well as origins of new topological invariants in the latter setup. Unique properties such as exceptional points and complex energy landscapes lead to new topological invariants including winding number/vorticity defined solely in the complex energy plane, and half-integer winding/Chern numbers. New forms of Kramers degeneracy appear here rendering distinct topological invariants. Modifications of adiabatic theory, time-evolution operator, biorthogonal bulk-boundary correspondence lead to unique features such as topological displacement of particles, 'skin-effect', and edge-selective attenuated and amplified topological polarizations without chiral symmetry. Extension and realization of topological ideas in photonic systems are mentioned. We conclude with discussions on relevant future directions, and highlight potential applications of some of these unique topological features of the non-Hermitian Hamiltonians.

Performance of missing transverse momentum reconstruction in proton-proton collisions at $\sqrt{s} =$ 13 TeV using the CMS detector

Abstract: The performance of missing transverse momentum (Tmiss) reconstruction algorithms for the CMS experiment is presented, using proton-proton collisions at a center-of-mass energy of 13 TeV, collected at the CERN LHC in 2016. The data sample corresponds to an integrated luminosity of 35.9 fb-1. The results include measurements of the scale and resolution of Tmiss, and detailed studies of events identified with anomalous Tmiss. The performance is presented of a Tmiss reconstruction algorithm that mitigates the effects of multiple proton-proton interactions, using the "pileup per particle identification" method. The performance is shown of an algorithm used to estimate the compatibility of the reconstructed Tmiss with the hypothesis that it originates from resolution effects.

Status and change of the cryosphere in the Extended Hindu Kush Himalaya Region

Abstract: The cryosphere is defined by the presence of frozen water in its many forms: glaciers, ice caps, ice sheets, snow, permafrost, and river and lake ice. In the extended Hindu Kush Himalaya (HKH) region, including the Pamirs, Tien Shan and Alatua, the cryosphere is a key freshwater resource, playing a vital and significant role in local and regional hydrology and ecology. Industry, agriculture, and hydroelectric power generation rely on timely and sufficient delivery of water in major river systems; changes in the cryospheric system may thus pose challenges for disaster risk reduction in the extended HKH region.

Direct Z-Scheme g-C3N4/FeWO4 Nanocomposite for Enhanced and Selective Photocatalytic CO2 Reduction under Visible Light

Abstract: Photocatalytic reduction of CO2 to renewable solar fuels is considered to be a promising strategy to simultaneously solve both global warming and energy crises. However, development of a superior p...

Genetic architecture of subcortical brain structures in 38,851 individuals

Abstract: Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

Combination of Searches for Higgs Boson Pair Production in Proton-Proton Collisions at √s = 13 TeV

Abstract: This Letter describes a search for Higgs boson pair production using the combined results from four final states: bbγγ, bbττ, bbbb, and bbVV, where V represents a W or Z boson. The search is performed using data collected in 2016 by the CMS experiment from LHC proton-proton collisions at s=13 TeV, corresponding to an integrated luminosity of 35.9 fb-1. Limits are set on the Higgs boson pair production cross section. A 95% confidence level observed (expected) upper limit on the nonresonant production cross section is set at 22.2 (12.8) times the standard model value. A search for narrow resonances decaying to Higgs boson pairs is also performed in the mass range 250–3000 GeV. No evidence for a signal is observed, and upper limits are set on the resonance production cross section.

Advanced Porous Materials for Sensing, Capture and Detoxification of Organic Pollutants toward Water Remediation

Abstract: Environmental pollution and its after-effects have become global concerns in recent years. Among all types of pollution, water pollution has been considered as a major threat in recent years; this problem will be even worse in the near future. In the 21st century, water recycling has become a crucial issue as more regions across the globe are witnessing a water crisis. Detoxification of wastewater via adsorptive removal or photocatalytic degradation for achieving purified and drinkable water has been determined as environmentally benign, energy economic and cost-effective. In this context, porous materials have gained enormous research consideration for detection of contaminants in effluents and for treatment of wastewater. A combination of high porosity, robustness and structural tunibility makes these nanosorbents stand out as materials in environmental remediation. Metal–organic frameworks, covalent organic frameworks and porous organic solids are among the versatile porous materials extensively invest...

Zinc ion interactions in a two-dimensional covalent organic framework based aqueous zinc ion battery

Abstract: The two-dimensional structural features of covalent organic frameworks (COFs) can promote the electrochemical storage of cations like H+, Li+, and Na+ through both faradaic and non-faradaic processes. However, the electrochemical storage of cations like Zn2+ ion is still unexplored although it bears a promising divalent charge. Herein, for the first time, we have utilized hydroquinone linked β-ketoenamine COF acting as a Zn2+ anchor in an aqueous rechargeable zinc ion battery. The charge-storage mechanism comprises of an efficient reversible interlayer interaction of Zn2+ ions with the functional moieties in the adjacent layers of COF (−182.0 kcal mol−1). Notably, due to the well-defined nanopores and structural organization, a constructed full cell, displays a discharge capacity as high as 276 mA h g−1 at a current rate of 125 mA g−1.

Generalizable Data-Free Objective for Crafting Universal Adversarial Perturbations

Abstract: Machine learning models are susceptible to adversarial perturbations: small changes to input that can cause large changes in output. It is also demonstrated that there exist input-agnostic perturbations, called universal adversarial perturbations, which can change the inference of target model on most of the data samples. However, existing methods to craft universal perturbations are (i) task specific, (ii) require samples from the training data distribution, and (iii) perform complex optimizations. Additionally, because of the data dependence, fooling ability of the crafted perturbations is proportional to the available training data. In this paper, we present a novel, generalizable and data-free approach for crafting universal adversarial perturbations. Independent of the underlying task, our objective achieves fooling via corrupting the extracted features at multiple layers. Therefore, the proposed objective is generalizable to craft image-agnostic perturbations across multiple vision tasks such as object recognition, semantic segmentation, and depth estimation. In the practical setting of black-box attack scenario (when the attacker does not have access to the target model and it's training data), we show that our objective outperforms the data dependent objectives to fool the learned models. Further, via exploiting simple priors related to the data distribution, our objective remarkably boosts the fooling ability of the crafted perturbations. Significant fooling rates achieved by our objective emphasize that the current deep learning models are now at an increased risk, since our objective generalizes across multiple tasks without the requirement of training data for crafting the perturbations. To encourage reproducible research, we have released the codes for our proposed algorithm.1

The fast, luminous ultraviolet transient AT2018cow: extreme supernova, or disruption of a star by an intermediate-mass black hole?

Abstract: Wide-field optical surveys have begun to uncover large samples of fast (t_rise 10 days. The spectrum remains extremely hot throughout its evolution, and the photospheric radius contracts with time (receding below R<10^14 cm after 1 month). This behavior does not match that of any known supernova, although a relativistic jet within a fallback supernova could explain some of the observed features. Alternatively, the transient could originate from the disruption of a star by an intermediate-mass black hole, although this would require long-lasting emission of highly super-Eddington thermal radiation. In either case, AT 2018cow suggests that the population of fast luminous transients represents a new class of astrophysical event. Intensive follow-up of this event in its late phases, and of any future events found at comparable distance, will be essential to better constrain their origins.

Crystal Engineering: An Outlook for the Future.

Abstract: Crystal Engineering has traditionally dealt with molecular crystals. It is the understanding of intermolecular interactions in the context of crystal packing and in the utilization of such understanding in the design of new solids with desired physical and chemical properties. We outline here five areas which come under the umbrella of Crystal Engineering and where we feel that a proper planning of research efforts could lead to higher dividends for science together with greater returns for humankind. We touch on themes and domains where science funding and translation efforts could be directed in the current climate of a society that increasingly expects applications and utility products from science and technology. The five topics are: 1) pharmaceutical solids; 2) industrial solid state reactions; 3) mechanical properties with practical applications; 4) MOFs and COFs framework solids; 5) new materials for solar energy harvesting and advanced polymers. © 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

Learning and Evaluating Contextual Embedding of Source Code

Abstract: Recent research has achieved impressive results on understanding and improving source code by building up on machine-learning techniques developed for natural languages. A significant advancement in natural-language understanding has come with the development of pre-trained contextual embeddings, such as BERT, which can be fine-tuned for downstream tasks with less labeled data and training budget, while achieving better accuracies. However, there is no attempt yet to obtain a high-quality contextual embedding of source code, and to evaluate it on multiple program-understanding tasks simultaneously; that is the gap that this paper aims to mitigate. Specifically, first, we curate a massive, deduplicated corpus of 7.4M Python files from GitHub, which we use to pre-train CuBERT, an open-sourced code-understanding BERT model; and, second, we create an open-sourced benchmark that comprises five classification tasks and one program-repair task, akin to code-understanding tasks proposed in the literature before. We fine-tune CuBERT on our benchmark tasks, and compare the resulting models to different variants of Word2Vec token embeddings, BiLSTM and Transformer models, as well as published state-of-the-art models, showing that CuBERT outperforms them all, even with shorter training, and with fewer labeled examples. Future work on source-code embedding can benefit from reusing our benchmark, and from comparing against CuBERT models as a strong baseline.

Search for supersymmetry in proton-proton collisions at 13 TeV in final states with jets and missing transverse momentum

Abstract: Results are reported from a search for supersymmetric particles in the final state with multiple jets and large missing transverse momentum. The search uses a sample of proton-proton collisions at $ \sqrt{s} $ = 13 TeV collected with the CMS detector in 2016–2018, corresponding to an integrated luminosity of 137 fb$^{−1}$, representing essentially the full LHC Run 2 data sample. The analysis is performed in a four-dimensional search region defined in terms of the number of jets, the number of tagged bottom quark jets, the scalar sum of jet transverse momenta, and the magnitude of the vector sum of jet transverse momenta. No significant excess in the event yield is observed relative to the expected background contributions from standard model processes. Limits on the pair production of gluinos and squarks are obtained in the framework of simplified models for supersymmetric particle production and decay processes. Assuming the lightest supersymmetric particle to be a neutralino, lower limits on the gluino mass as large as 2000 to 2310 GeV are obtained at 95% confidence level, while lower limits on the squark mass as large as 1190 to 1630 GeV are obtained, depending on the production scenario.