Synthesis from zinc oxalate, growth mechanism and optical properties of ZnO nano/micro structures

We report the synthesis of various morphological micro to nano structured zinc oxide crystals via simple precipitation technique. The growth mechanisms of the zinc oxide nanostructures such as snowflake, rose, platelets, porous pyramid and rectangular shapes were studied in detail under various growth conditions. The precursor powders were prepared using several zinc counter ions such as chloride, nitrate and sulphate along with oxalic acid as a precipitating agent. The precursors were decomposed by heating in air resulting in the formation of different shapes of zinc oxide crystals. Variations in ZnO nanostructural shapes were possibly due to the counter ion effect. Sulphate counter ion led to unusual rose-shape morphology. Strong ultrasonic treatment on ZnO rose shows that it was formed by irregular arrangement of micro to nano size hexagonal zinc oxide platelets. The X-ray diffraction studies confirmed the wurzite structure of all zinc oxide samples synthesized using different zinc counter ions. Functional groups of the zinc oxalate precursor and zinc oxide were identified using micro Raman studies. The blue light emission spectra of the various morphologies were recorded using luminescence spectrometer. (C) 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Self-Assembly of Metallamacrocycles Using a Dinuclear Organometallic Acceptor: Synthesis, Characterization, and Sensing Study

A dinuclear organometallic acceptor 4,4'-bis[trans-Pt(PEt(3))(2)(O(3)SCF(3))(ethynyl)]biphenyl (1) containing Pt-ethynyl functionality is synthesized. Multinuclear NMR ((1)H, (31)P, and (13)C), infrared (IR), and electrospray ionization mass spectrometry (ESI-MS) including single-crystal X-ray diffraction analysis established the formation of 1. Equimolar treatment of acceptor 1 separately with three different ``clip'' type ditopic donors (L(a)-L(c)) yielded [2 + 2] self-assembled three metallamacrocycles 2a-2c, respectively. These macrocycles were characterized by various spectroscopic techniques, and their sizes/shapes were obtained through geometry optimization using molecular mechanics universal force field (MMUFF) simulations. Attachment of unsaturated ethynyl functionality to biphenyl building unit helped to make the macrocycles (2a-2c) pi-electron rich and thereby fluorescent in nature. Furthermore, 2c in solution has been examined to be suitable for sensing electron-deficient nitroaromatic like picric acid, which is often considered as a secondary chemical explosive. The fluorescence study of 2c showed a marked quenching of initial emission intensity upon titrating with picric acid (PA), and it exhibited the largest fluorescence quenching response with high selectivity among various other electron deficient aromatic compounds tested.

Comparison of 10 Multi-Sensor Image Fusion Paradigms for IKONOS Images

Fusion of multi-sensor imaging data enables a synergetic interpretation of complementary information obtained by sensors of different spectral ranges. Multi-sensor data of diverse spectral, spatial and temporal resolutions require advanced numerical techniques for analysis and interpretation. This paper reviews ten advanced pixel based image fusion techniques – Component substitution (COS), Local mean and variance matching, Modified IHS (Intensity Hue Saturation), Fast Fourier Transformed-enhanced IHS, Laplacian Pyramid, Local regression, Smoothing filter (SF), Sparkle, SVHC and Synthetic Variable Ratio. The above techniques were tested on IKONOS data (Panchromatic band at 1 m spatial resolution and Multispectral 4 bands at 4 m spatial resolution). Evaluation of the fused results through various accuracy measures, revealed that SF and COS methods produce images closest to corresponding multi-sensor would observe at the highest resolution level (1 m).

Spatio-temporal landscape modelling for natural hazard vulnerability analysis in select watersheds of Central Western Ghats

Natural hazards such as landslides are triggered by numerous factors such as ground movements, rock falls, slope failure, debris flows, slope instability, etc. Changes in slope stability happen due to human intervention, anthropogenic activities, change in soil structure, loss or absence of vegetation (changes in land cover), etc. Loss of vegetation happens when the forest is fragmented due to anthropogenic activities. Hence land cover mapping with forest fragmentation can provide vital information for visualising the regions that require immediate attention from slope stability aspects. The main objective of this paper is to understand the rate of change in forest landscape from 1973 to 2004 through multi-sensor remote sensing data analysis. The forest fragmentation index presented here is based on temporal land use information and forest fragmentation model, in which the forest pixels are classified as patch, transitional, edge, perforated, and interior, that give a measure of forest continuity. The analysis carried out for five prominent watersheds of Uttara Kannada district– Aganashini, Bedthi, Kali, Sharavathi and Venkatpura revealed that interior forest is continuously decreasing while patch, transitional, edge and perforated forest show increasing trend. The effect of forest fragmentation on landslide occurrence was visualised by overlaying the landslide occurrence points on classified image and forest fragmentation map. The increasing patch and transitional forest on hill slopes are the areas prone to landslides, evident from the field verification, indicating that deforestation is a major triggering factor for landslides. This emphasises the need for immediate conservation measures for sustainable management of the landscape. Quantifying and describing land use - land cover change and fragmentation is crucial for assessing the effect of land management policies and environmental protection decisions.

Pillar height dependent formation of unprecedented Pd-8 molecular swing and Pd-6 molecular boat via multicomponent self-assembly

Three-component self-assembly of a cis-blocked 90 degrees Pd(II) acceptor with a mixture of a tetraimidazole and a linear dipyridyl donor self-discriminated into unusual Pd-8 molecular swing (1) and Pd-6 molecular boat (2), which are characterized by single-crystal X-ray diffraction analysis; their ability to bind C-60 in solution is established by fluorescence titration.

Withania somnifera reverses Alzheimer's disease pathology by enhancing low-density lipoprotein receptor-related protein in liver

A 30-d course of oral administration of a semipurified extract of the root of Withania somnifera consisting predominantly of withanolides and withanosides reversed behavioral deficits, plaque pathology, accumulation of beta-amyloid peptides (A beta) and oligomers in the brains of middle-aged and old APP/PS1 Alzheimer's disease transgenic mice. It was similarly effective in reversing behavioral deficits and plaque load in APPSwInd mice (line J20). The temporal sequence involved an increase in plasma A beta and a decrease in brain A beta monomer after 7 d, indicating increased transport of A beta from the brain to the periphery. Enhanced expression of low-density lipoprotein receptor-related protein (LRP) in brain microvessels and the A beta-degrading protease neprilysin (NEP) occurred 14-21 d after a substantial decrease in brain A beta levels. However, significant increase in liver LRP and NEP occurred much earlier, at 7 d, and were accompanied by a rise in plasma sLRP, a peripheral sink for brain A beta. In WT mice, the extract induced liver, but not brain, LRP and NEP and decreased plasma and brain A beta, indicating that increase in liver LRP and sLRP occurring independent of A beta concentration could result in clearance of A beta. Selective down-regulation of liver LRP, but not NEP, abrogated the therapeutic effects of the extract. The remarkable therapeutic effect of W. somnifera mediated through up-regulation of liver LRP indicates that targeting the periphery offers a unique mechanism for A beta clearance and reverses the behavioral deficits and pathology seen in Alzheimer's disease models.

Radiative effects of elevated aerosol layer in Central Himalayas

Systematic observations of light detection and ranging (LIDAR) to detect elevated aerosol layer were carried out at Manora Peak (29.4 degrees N, 79.5 degrees E, similar to 1960 m a.s.l), Nainital, in the Central Himalayas during January-May 2008. In spite of being a remote, high-altitude site, an elevated aerosol layer is observed quite frequently in the altitude range of 2460-4460 m a.s.l with a width of similar to 2 km during the observation period. We compare these profiles with the vertical profiles observed over Gadanki (13.5 degrees N, 79.2 degrees E, similar to 370 m a.s.l), a tropical station, where no such elevated aerosol layer was found. Further, there is a steady increase in aerosol optical depth (AOD) from January (winter) to May (summer) from 0.043 to 0.742, respectively, at Manora Peak, indicating aerosol loading in the atmosphere. Our observations show north-westerly winds indicating the convective lifting of aerosols from far-off regions followed by horizontal long-range transport. The presence of strongly absorbing and scattering aerosols in the elevated layer resulted in a relatively large diurnal mean aerosol surface radiative forcing efficiency (forcing per unit optical depth) of about -65 and -63 W m(-2) and the corresponding mean reduction in the observed net solar flux at the surface (cooling effect) is as high as -22 and -30 W m(-2). The reduction of radiation will heat the lower atmosphere by redistributing the radiation with heating rate of 1.13 and 1.31 K day(-1) for April and May 2008, respectively, in the lower atmosphere.

Climatic fluctuations during the LIA and post-LIA in the Kumaun Lesser Himalaya, India: Evidence from a 400 y old stalagmite record

This paper presents the first stable isotope (delta O-18 and delta C-13) data of a similar to 400 years (1590-2006 AD) long annual to decadal-resolution speleothem record collected from the Indian Lesser Himalaya. The data show a variation from -2.7 to -5.9 parts per thousand in delta O-18 and -5.3 to -8.8 parts per thousand in delta C-13. The isotopic analyses indicate that the climate during this period can be divided into two stages: a wet phase during the Little Ice Age (LIA) (1590-1850 AD) and comparatively dry phase during the post-LIA after 1850 AD. However, the record also documents the minor dry events during the LIA and a wet episode after the LIA. Within the age uncertainty, the dry spells during the LIA are linked with the historical drought events in the Indian subcontinent and similar latitudes. The isotopic record is consistent with a number of previous studies in the areas influenced by the Westerlies but appears to be conflicting to the regions, dominated by the Indian Summer Monsoon (ISM). This may be due to the possible changes in the strength of Westerlies in the study area and added by negative anomaly of North Atlantic Oscillation (NAO) during the LIA. (C) 2012 Elsevier Ltd and INQUA. All rights reserved.

Cross-Guided Clustering: Transfer of Relevant Supervision across Tasks

Lack of supervision in clustering algorithms often leads to clusters that are not useful or interesting to human reviewers. We investigate if supervision can be automatically transferred for clustering a target task, by providing a relevant supervised partitioning of a dataset from a different source task. The target clustering is made more meaningful for the human user by trading-off intrinsic clustering goodness on the target task for alignment with relevant supervised partitions in the source task, wherever possible. We propose a cross-guided clustering algorithm that builds on traditional k-means by aligning the target clusters with source partitions. The alignment process makes use of a cross-task similarity measure that discovers hidden relationships across tasks. When the source and target tasks correspond to different domains with potentially different vocabularies, we propose a projection approach using pivot vocabularies for the cross-domain similarity measure. Using multiple real-world and synthetic datasets, we show that our approach improves clustering accuracy significantly over traditional k-means and state-of-the-art semi-supervised clustering baselines, over a wide range of data characteristics and parameter settings.

Coalescent Method in Conjunction with Niche Modeling Reveals Cryptic Diversity among Centipedes in the Western Ghats of South India

Background: There has been growing interest in integrative taxonomy that uses data from multiple disciplines for species delimitation. Typically, in such studies, monophyly is taken as a proxy for taxonomic distinctiveness and these units are treated as potential species. However, monophyly could arise due to stochastic processes. Thus here, we have employed a recently developed tool based on coalescent approach to ascertain the taxonomic distinctiveness of various monophyletic units. Subsequently, the species status of these taxonomic units was further tested using corroborative evidence from morphology and ecology. This inter-disciplinary approach was implemented on endemic centipedes of the genus Digitipes (Attems 1930) from the Western Ghats (WG) biodiversity hotspot of India. The species of the genus Digitipes are morphologically conserved, despite their ancient late Cretaceous origin. Principal Findings: Our coalescent analysis based on mitochondrial dataset indicated the presence of nine putative species. The integrative approach, which includes nuclear, morphology, and climate datasets supported distinctiveness of eight putative species, of which three represent described species and five were new species. Among the five new species, three were morphologically cryptic species, emphasizing the effectiveness of this approach in discovering cryptic diversity in less explored areas of the tropics like the WG. In addition, species pairs showed variable divergence along the molecular, morphological and climate axes. Conclusions: A multidisciplinary approach illustrated here is successful in discovering cryptic diversity with an indication that the current estimates of invertebrate species richness for the WG might have been underestimated. Additionally, the importance of measuring multiple secondary properties of species while defining species boundaries was highlighted given variable divergence of each species pair across the disciplines.

Understanding the Magnetization Reversal in Six-Fold Anisotropic Hexagonal Networks

Isolated magnetic nanowires have been studied extensively and the magnetization reversal mechanism is well understood in these systems. But when these nanowires are joined together in different architectures, they behave differently and can give novel properties. Using this approach, one can engineer the network architectures to get artificial anisotropy. Here, we report six-fold anisotropy by joining the magnetic nanowires into hexagonal network. For this study, we also benchmark the widely used micromagnetic packages: OOMMF, Nmag, and LLG-simulator. Further, we propose a local hysteresis method by post processing the spatial magnetization information. With this approach we obtained the hysteresis of nanowires to understand the six-fold anisotropy and the reversal mechanism within the hexagonal networks.

Multi-model climate change projections for India under representative concentration pathways

Climate projections for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) are made using the newly developed representative concentration pathways (RCPs) under the Coupled Model Inter-comparison Project 5 (CMIP5). This article provides multi-model and multi-scenario temperature and precipitation projections for India for the period 1860-2099 based on the new climate data. We find that CMIP5 ensemble mean climate is closer to observed climate than any individual model. The key findings of this study are: (i) under the business-as-usual (between RCP6.0 and RCP8.5) scenario, mean warming in India is likely to be in the range 1.7-2 degrees C by 2030s and 3.3-4.8 degrees C by 2080s relative to pre-industrial times; (ii) all-India precipitation under the business-as-usual scenario is projected to increase from 4% to 5% by 2030s and from 6% to 14% towards the end of the century (2080s) compared to the 1961-1990 baseline; (iii) while precipitation projections are generally less reliable than temperature projections, model agreement in precipitation projections increases from RCP2.6 to RCP8.5, and from short-to long-term projections, indicating that long-term precipitation projections are generally more robust than their short-term counterparts and (iv) there is a consistent positive trend in frequency of extreme precipitation days (e.g. > 40 mm/day) for decades 2060s and beyond. These new climate projections should be used in future assessment of impact of climate change and adaptation planning. There is need to consider not just the mean climate projections, but also the more important extreme projections in impact studies and as well in adaptation planning.