Showing papers by "Indian Institute of Science published in 2015"

Combined Measurement of the Higgs Boson Mass in pp Collisions at √s=7 and 8 TeV with the ATLAS and CMS Experiments

Abstract: A measurement of the Higgs boson mass is presented based on the combined data samples of the ATLAS and CMS experiments at the CERN LHC in the H→γγ and H→ZZ→4l decay channels. The results are obtained from a simultaneous fit to the reconstructed invariant mass peaks in the two channels and for the two experiments. The measured masses from the individual channels and the two experiments are found to be consistent among themselves. The combined measured mass of the Higgs boson is mH=125.09±0.21 (stat)±0.11 (syst) GeV.

Colloidal CsPbBr3 Perovskite Nanocrystals: Luminescence beyond Traditional Quantum Dots.

Abstract: Traditional CdSe-based colloidal quantum dots (cQDs) have interesting photoluminescence (PL) properties. Herein we highlight the advantages in both ensemble and single-nanocrystal PL of colloidal CsPbBr3 nanocrystals (NCs) over the traditional cQDs. An ensemble of colloidal CsPbBr3 NCs (11 nm) exhibits ca. 90 % PL quantum yield with narrow (FWHM=86 meV) spectral width. Interestingly, the spectral width of a single-NC and an ensemble are almost identical, ruling out the problem of size-distribution in PL broadening. Eliminating this problem leads to a negligible influence of self-absorption and Forster resonance energy transfer, along with batch-to-batch reproducibility of NCs exhibiting PL peaks within ±1 nm. Also, PL peak positions do not alter with measurement temperature in the range of 25 to 100 °C. Importantly, CsPbBr3 NCs exhibit suppressed PL blinking with ca. 90 % of the individual NCs remain mostly emissive (on-time >85 %), without much influence of excitation power.

Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 TeV

Abstract: Properties of the Higgs boson with mass near 125 GeV are measured in proton-proton collisions with the CMS experiment at the LHC. Comprehensive sets of production and decay measurements are combined. The decay channels include gamma gamma, ZZ, WW, tau tau, bb, and mu mu pairs. The data samples were collected in 2011 and 2012 and correspond to integrated luminosities of up to 5.1 inverse femtobarns at 7 TeV and up to 19.7 inverse femtobarns at 8 TeV. From the high-resolution gamma gamma and ZZ channels, the mass of the Higgs boson is determined to be 125.02 +0.26 -0.27 (stat) +0.14 -0.15 (syst) GeV. For this mass value, the event yields obtained in the different analyses tagging specific decay channels and production mechanisms are consistent with those expected for the standard model Higgs boson. The combined best-fit signal relative to the standard model expectation is 1.00 +/- 0.09 (stat) +0.08 -0.07 (theo) +/- 0.07 (syst) at the measured mass. The couplings of the Higgs boson are probed for deviations in magnitude from the standard model predictions in multiple ways, including searches for invisible and undetected decays. No significant deviations are found.

Zinc oxide based photocatalysis: tailoring surface-bulk structure and related interfacial charge carrier dynamics for better environmental applications

Abstract: As an alternative to the gold standard TiO2 photocatalyst, the use of zinc oxide (ZnO) as a robust candidate for wastewater treatment is widespread due to its similarity in charge carrier dynamics upon bandgap excitation and the generation of reactive oxygen species in aqueous suspensions with TiO2. However, the large bandgap of ZnO, the massive charge carrier recombination, and the photoinduced corrosion–dissolution at extreme pH conditions, together with the formation of inert Zn(OH)2 during photocatalytic reactions act as barriers for its extensive applicability. To this end, research has been intensified to improve the performance of ZnO by tailoring its surface-bulk structure and by altering its photogenerated charge transfer pathways with an intention to inhibit the surface-bulk charge carrier recombination. For the first time, the several strategies, such as tailoring the intrinsic defects, surface modification with organic compounds, doping with foreign ions, noble metal deposition, heterostructuring with other semiconductors and modification with carbon nanostructures, which have been successfully employed to improve the photoactivity and stability of ZnO are critically reviewed. Such modifications enhance the charge separation and facilitate the generation of reactive oxygenated free radicals, and also the interaction with the pollutant molecules. The synthetic route to obtain hierarchical nanostructured morphologies and study their impact on the photocatalytic performance is explained by considering the morphological influence and the defect-rich chemistry of ZnO. Finally, the crystal facet engineering of polar and non-polar facets and their relevance in photocatalysis is outlined. It is with this intention that the present review directs the further design, tailoring and tuning of the physico-chemical and optoelectronic properties of ZnO for better applications, ranging from photocatalysis to photovoltaics.

Bioenergy and climate change mitigation: an assessment.

Abstract: Bioenergy deployment offers significant potential for climate change mitigation, but also carries considerable risks. In this review, we bring together perspectives of various communities involved in the research and regulation of bioenergy deployment in the context of climate change mitigation: Land-use and energy experts, land-use and integrated assessment modelers, human geographers, ecosystem researchers, climate scientists and two different strands of life-cycle assessment experts. We summarize technological options, outline the state-of-the-art knowledge on various climate effects, provide an update on estimates of technical resource potential and comprehensively identify sustainability effects. Cellulosic feedstocks, increased end-use efficiency, improved land carbon-stock management and residue use, and, when fully developed, BECCS appear as the most promising options, depending on development costs, implementation, learning, and risk management. Combined heat and power, efficient biomass cookstoves and small-scale power generation for rural areas can help to promote energy access and sustainable development, along with reduced emissions. We estimate the sustainable technical potential as up to 100EJ: high agreement; 100-300EJ: medium agreement; above 300EJ: low agreement. Stabilization scenarios indicate that bioenergy may supply from 10 to 245EJyr(-1) to global primary energy supply by 2050. Models indicate that, if technological and governance preconditions are met, large-scale deployment (>200EJ), together with BECCS, could help to keep global warming below 2 degrees degrees of preindustrial levels; but such high deployment of land-intensive bioenergy feedstocks could also lead to detrimental climate effects, negatively impact ecosystems, biodiversity and livelihoods. The integration of bioenergy systems into agriculture and forest landscapes can improve land and water use efficiency and help address concerns about environmental impacts. We conclude that the high variability in pathways, uncertainties in technological development and ambiguity in political decision render forecasts on deployment levels and climate effects very difficult. However, uncertainty about projections should not preclude pursuing beneficial bioenergy options.

Achieving Highly Efficient, Selective, and Stable CO2 Reduction on Nitrogen-Doped Carbon Nanotubes.

Abstract: The challenge in the electrosynthesis of fuels from CO2 is to achieve durable and active performance with cost-effective catalysts. Here, we report that carbon nanotubes (CNTs), doped with nitrogen to form resident electron-rich defects, can act as highly efficient and, more importantly, stable catalysts for the conversion of CO2 to CO. The unprecedented overpotential (-0.18 V) and selectivity (80%) observed on nitrogen-doped CNTs (NCNTs) are attributed to their unique features to facilitate the reaction, including (i) high electrical conductivity, (ii) preferable catalytic sites (pyridinic N defects), and (iii) low free energy for CO2 activation and high barrier for hydrogen evolution. Indeed, DFT calculations show a low free energy barrier for the potential-limiting step to form key intermediate COOH as well as strong binding energy of adsorbed COOH and weak binding energy for the adsorbed CO. The highest selective site toward CO production is pyridinic N, and the NCNT-based electrodes exhibit no degradation over 10 h of continuous operation, suggesting the structural stability of the electrode.

CTFS-ForestGEO: A worldwide network monitoring forests in an era of global change

Abstract: Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses to global change. Within very large plots (median size 25ha), all stems 1cm diameter are identified to species, mapped, and regularly recensused according to standardized protocols. CTFS-ForestGEO spans 25 degrees S-61 degrees N latitude, is generally representative of the range of bioclimatic, edaphic, and topographic conditions experienced by forests worldwide, and is the only forest monitoring network that applies a standardized protocol to each of the world's major forest biomes. Supplementary standardized measurements at subsets of the sites provide additional information on plants, animals, and ecosystem and environmental variables. CTFS-ForestGEO sites are experiencing multifaceted anthropogenic global change pressures including warming (average 0.61 degrees C), changes in precipitation (up to +/- 30% change), atmospheric deposition of nitrogen and sulfur compounds (up to 3.8g Nm(-2)yr(-1) and 3.1g Sm(-2)yr(-1)), and forest fragmentation in the surrounding landscape (up to 88% reduced tree cover within 5km). The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics. Ongoing research across the CTFS-ForestGEO network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change.

Review of multidimensional data processing approaches for Raman and infrared spectroscopy

Abstract: Raman and Infrared (IR) spectroscopies provide information about the structure, functional groups and environment of the molecules in the sample. In combination with a microscope, these techniques can also be used to study molecular distributions in heterogeneous samples. Over the past few decades Raman and IR microspectroscopy based techniques have been extensively used to understand fundamental biology and responses of living systems under diverse physiological and pathological conditions. The spectra from biological systems are complex and diverse, owing to their heterogeneous nature consisting of bio-molecules such as proteins, lipids, nucleic acids, carbohydrates etc. Sometimes minor differences may contain critical information. Therefore, interpretation of the results obtained from Raman and IR spectroscopy is difficult and to overcome these intricacies and for deeper insight we need to employ various data mining methods. These methods must be suitable for handling large multidimensional data sets and for exploring the complete spectral information simultaneously. The effective implementation of these multivariate data analysis methods requires the pretreatment of data. The preprocessing of raw data helps in the elimination of noise (unwanted signals) and the enhancement of discriminating features. This review provides an outline of the state-of-the-art data processing tools for multivariate analysis and the various preprocessing methods that are widely used in Raman and IR spectroscopy including imaging for better qualitative and quantitative analysis of biological samples.

Data-free parameter pruning for Deep Neural Networks

Abstract: Deep Neural nets (NNs) with millions of parameters are at the heart of many state-of-the-art computer vision systems today. However, recent works have shown that much smaller models can achieve similar levels of performance. In this work, we address the problem of pruning parameters in a trained NN model. Instead of removing individual weights one at a time as done in previous works, we remove one neuron at a time. We show how similar neurons are redundant, and propose a systematic way to remove them. Unlike previous works, our pruning method does not require access to any training/validation data.

An estimate of the number of tropical tree species

Abstract: The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher's alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between similar to 40,000 and similar to 53,000, i.e., at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of similar to 19,000-25,000 tree species. Continental Africa is relatively depauperate with a minimum of similar to 4,500-6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa.

Never-ending learning

Abstract: Whereas people learn many different types of knowledge from diverse experiences over many years, most current machine learning systems acquire just a single function or data model from just a single data set We propose a never-ending learning paradigm for machine learning, to better reflect the more ambitious and encompassing type of learning performed by humans As a case study, we describe the Never-Ending Language Learner (NELL), which achieves some of the desired properties of a never-ending learner, and we discuss lessons learned NELL has been learning to read the web 24 hours/day since January 2010, and so far has acquired a knowledge base with over 80 million confidence-weighted beliefs (eg, servedWith(tea, biscuits)), while learning continually to improve its reading competence over time NELL has also learned to reason over its knowledge base to infer new beliefs from old ones, and is now beginning to extend its ontology by synthesizing new relational predicates NELL can be tracked online at http://rtwmlcmuedu, and followed on Twitter at @CMUNELL

Data-free parameter pruning for Deep Neural Networks

Abstract: Deep Neural nets (NNs) with millions of parameters are at the heart of many state-of-the-art computer vision systems today. However, recent works have shown that much smaller models can achieve similar levels of performance. In this work, we address the problem of pruning parameters in a trained NN model. Instead of removing individual weights one at a time as done in previous works, we remove one neuron at a time. We show how similar neurons are redundant, and propose a systematic way to remove them. Our experiments in pruning the densely connected layers show that we can remove upto 85\% of the total parameters in an MNIST-trained network, and about 35\% for AlexNet without significantly affecting performance. Our method can be applied on top of most networks with a fully connected layer to give a smaller network.

Direct evidence for dominant bond-directional interactions in a honeycomb lattice iridate Na2IrO3

Abstract: Honeycomb iridates have been proposed as experimental realizations of the Kitaev model. An X-ray scattering study presents evidence for bond-directional interactions in Na2IrO3, a key requirement to make the connection with Kitaev physics possible.

Selective and Sensitive Aqueous-Phase Detection of 2,4,6-Trinitrophenol (TNP) by an Amine-Functionalized Metal–Organic Framework

Abstract: Highly selective and sensitive aqueous-phase detection of nitro explosive 2,4,6-trinitrophenol (TNP) by a hydrolytically stable 3D luminescent metal-organic framework is reported. The compound senses TNP exclusively even in the presence of other nitro-compounds, with an unprecedented sensitivity in the MOF regime by means of strategic deployment of its free amine groups. Such an accurate sensing of TNP, widely recognized as a harmful environmental contaminant in water media, establishes this new strategic approach as one of the frontiers to tackle present-day security and health concerns in a real-time scenario.

Pressure-dependent optical and vibrational properties of monolayer molybdenum disulfide.

Abstract: Controlling the band gap by tuning the lattice structure through pressure engineering is a relatively new route for tailoring the optoelectronic properties of two-dimensional (2D) materials Here, we investigate the electronic structure and lattice vibrational dynamics of the distorted monolayer 1T-MoS2 (1T′) and the monolayer 2H-MoS2 via a diamond anvil cell (DAC) and density functional theory (DFT) calculations The direct optical band gap of the monolayer 2H-MoS2 increases by 117% from 185 to 208 eV, which is the highest reported for a 2D transition metal dichalcogenide (TMD) material DFT calculations reveal a subsequent decrease in the band gap with eventual metallization of the monolayer 2H-MoS2, an overall complex structure–property relation due to the rich band structure of MoS2 Remarkably, the metastable 1T′-MoS2 metallic state remains invariant with pressure, with the J2, A1g, and E2g modes becoming dominant at high pressures This substantial reversible tunability of the electronic and vibr

Predicting clinical response to anticancer drugs using an ex vivo platform that captures tumour heterogeneity

Abstract: Predicting clinical response to anticancer drugs remains a major challenge in cancer treatment. Emerging reports indicate that the tumour microenvironment and heterogeneity can limit the predictive power of current biomarker-guided strategies for chemotherapy. Here we report the engineering of personalized tumour ecosystems that contextually conserve the tumour heterogeneity, and phenocopy the tumour microenvironment using tumour explants maintained in defined tumour grade-matched matrix support and autologous patient serum. The functional response of tumour ecosystems, engineered from 109 patients, to anticancer drugs, together with the corresponding clinical outcomes, is used to train a machine learning algorithm; the learned model is then applied to predict the clinical response in an independent validation group of 55 patients, where we achieve 100% sensitivity in predictions while keeping specificity in a desired high range. The tumour ecosystem and algorithm, together termed the CANScript technology, can emerge as a powerful platform for enabling personalized medicine.

Search for a Higgs boson in the mass range from 145 to 1000 GeV decaying to a pair of W or Z bosons

Abstract: A search for a heavy Higgs boson in the H to WW and H to ZZ decay channels is reported. The search is based upon proton-proton collision data samples corresponding to an integrated luminosity of up to 5.1 inverse femtobarns at sqrt(s)=7 TeV and up to 19.7 inverse femtobarns at sqrt(s)=8 TeV, recorded by the CMS experiment at the CERN LHC. Several final states of the H to WW and H to ZZ decays are analyzed. The combined upper limit at the 95% confidence level on the product of the cross section and branching fraction exclude a Higgs boson with standard model-like couplings and decays in the range 145 < m[H] < 1000 GeV. We also interpret the results in the context of an electroweak singlet extension of the standard model.

Spatially resolved analysis of short-range structure perturbations in a plastically bent molecular crystal

Abstract: The exceptional mechanical flexibility observed with certain organic crystals defies the common perception of single crystals as brittle objects. Here, we describe the morphostructural consequences of plastic deformation in crystals of hexachlorobenzene that can be bent mechanically at multiple locations to 360° with retention of macroscopic integrity. This extraordinary plasticity proceeds by segregation of the bent section into flexible layers that slide on top of each other, thereby generating domains with slightly different lattice orientations. Microscopic, spectroscopic and diffraction analyses of the bent crystal showed that the preservation of crystal integrity when stress is applied on the (001) face requires sliding of layers by breaking and re-formation of halogen-halogen interactions. Application of stress on the (100) face, in the direction where π···π interactions dominate the packing, leads to immediate crystal disintegration. Within a broader perspective, this study highlights the yet unrecognized extraordinary malleability of molecular crystals with strongly anisotropic supramolecular interactions.

Insulin-Like Growth Factor System in Cancer: Novel Targeted Therapies

Abstract: Insulin-like growth factors (IGFs) are essential for growth and survival that suppress apoptosis and promote cell cycle progression, angiogenesis, and metastatic activities in various cancers. The IGFs actions are mediated through the IGF-1 receptor that is involved in cell transformation induced by tumour. These effects depend on the bioavailability of IGFs, which is regulated by IGF binding proteins (IGFBPs). We describe here the role of the IGF system in cancer, proposing new strategies targeting this system. We have attempted to expand the general viewpoint on IGF-1R, its inhibitors, potential limitations of IGF-1R, antibodies and tyrosine kinase inhibitors, and IGFBP actions. This review discusses the emerging view that blocking IGF via IGFBP is a better option than blocking IGF receptors. This can lead to the development of novel cancer therapies.

Metal complexes of curcumin for cellular imaging, targeting, and photoinduced anticancer activity.

Abstract: CONSPECTUS: Curcumin is a polyphenolic species. As an active ingredient of turmeric, it is well-known for its traditional medicinal properties. The therapeutic values include antioxidant, anti-inflammatory, antiseptic, and anticancer activity with the last being primarily due to inhibition of the transcription factor NF-kappa B besides affecting several biological pathways to arrest tumor growth and its progression. Curcumin with all these positive qualities has only remained a potential candidate for cancer treatment over the years without seeing any proper usage because of its hydrolytic instability involving the diketo moiety in a cellular medium and its poor bioavailability. The situation has changed considerably in recent years with the observation that curcumin in monoanionic form could be stabilized on binding to a metal ion. The reports from our group and other groups have shown that curcumin in the metal-bound form retains its therapeutic potential. This has opened up new avenues to develop curcumin-based metal complexes as anticancer agents. Zinc(II) complexes of curcumin are shown to be stable in a cellular medium. They display moderate cytotoxicity against prostate cancer and neuroblastoma cell lines. A similar stabilization and cytotoxic effect is reported for (arene)ruthenium(II) complexes of curcumin against a variety of cell lines. The half-sandwich 1,3,5-triaza-7-phosphatricyclo-3.3.1.1]decane (RAPTA)-type ruthenium(II) complexes of curcumin are shown to be promising cytotoxic agents with low micromolar concentrations for a series of cancer cell lines. In a different approach, cobalt(III) complexes of curcumin are used for its cellular delivery in hypoxic tumor cells using intracellular agents that reduce the metal and release curcumin as a cytotoxin. Utilizing the photophysical and photochemical properties of the curcumin dye, we have designed and synthesized photoactive curcumin metal complexes that are used for cellular imaging by fluorescence microscopy and damaging the cancer cells on photoactivation in visible light while being minimally toxic in darkness. In this Account, we have made an attempt to review the current status of the chemistry of metal curcumin complexes and present results from our recent studies on curcumin complexes showing remarkable in vitro photocytotoxicity. The undesirable dark toxicity of the complexes can be reduced with suitable choice of the metal and the ancillary ligands in a ternary structure. The complexes can be directed to specific subcellular organelles. Selectivity by targeting cancer cells over normal cells can be achieved with suitable ligand design. We expect that this methodology is likely to provide an impetus toward developing curcumin-based photochemotherapeutics for anticancer treatment and cure.

Multifarious facets of sugar-derived molecular gels: molecular features, mechanisms of self-assembly and emerging applications

Abstract: The remarkable capability of nature to design and create excellent self-assembled nano-structures, especially in the biological world, has motivated chemists to mimic such systems with synthetic molecular and supramolecular systems. The hierarchically organized self-assembly of low molecular weight gelators (LMWGs) based on non-covalent interactions has been proven to be a useful tool in the development of well-defined nanostructures. Among these, the self-assembly of sugar-derived LMWGs has received immense attention because of their propensity to furnish biocompatible, hierarchical, supramolecular architectures that are macroscopically expressed in gel formation. This review sheds light on various aspects of sugar-derived LMWGs, uncovering their mechanisms of gelation, structural analysis, and tailorable properties, and their diverse applications such as stimuli-responsiveness, sensing, self-healing, environmental problems, and nano and biomaterials synthesis.

The n → π* interaction: a rapidly emerging non-covalent interaction

Abstract: This perspective describes the current status of a recently discovered non-covalent interaction named as the n → π* interaction, which is very weak and counterintuitive in nature. In this review, we have provided a brief overview of the widespread presence of this interaction in biomacromolecules, small biomolecules and materials, as well as the physical nature of this interaction explored using various experimental and theoretical techniques. It has been found that this interaction is equally important to other non-covalent interactions for the stability and specific structures of biomolecules and materials. An in-depth understanding of this interaction can help in designing more efficient functional materials as well as drugs. The review also provides a future outlook in terms of exploring the detailed functional role of this interaction in biological processes and its direct spectroscopic evidence, which other commonly known non-covalent interactions (conventional hydrogen bonding, π-hydrogen bonding, π-stacking, etc.) have.