Unparticle Decay of Neutrinos and its Possible Signatures at a Km2{\rm Km}^2 Detector for (3+1) Flavour Framework

We consider a scenario where ultra high energy neutrinos undergo unparticle decay during its passage from its cosmological source to Earth. The idea of unparticle had been first proposed by Georgi by considering the possible existence of an unknown scale invariant sector at high energies and the unparticles in this sector manifest itself below a dimensional transmutation scale $\Lambda_{\cal U}$. We then explore the possible signature of such decaying neutrinos to unparticles at a square kilometer detector such as IceCube.Comment: 20 pages LaTeX, 5 eps figure

Investments in irrigation projects - an impact analysis

Physical infrastructure development is a powerful means of promoting economic growth as (i) it creates production facilities, “crowds in†private investment and thereby stimulates economic activities, (ii) reduces transaction and marketing costs, improving competitiveness, and (iii) provides employment opportunities to the poor. Rural Infrastructure Development Fund (RIDF) supported irrigation projects help provide the necessary impetus for infrastructure development, thereby aiding in capital formation. Evaluation of irrigation investments under RIDF in the states of Uttar Pradesh, Haryana, Orissa, Maharashtra and Assam has revealed that the investments are economically viable. The net benefits realised by the user community from the investments in irrigation have been found fairly high, except in Orissa and Uttar Pradesh. Full benefits of medium irrigation projects in Uttar Pradesh could not be realised due to pending rehabilitation work and scanty rainfall. Similarly, non-completion of canal works in Orissa has adversely affected the returns to investment. The study has observed that adequate maintenance through budgetary provisions and/or through levying of user charges would ensure sustainability of benefits. It has suggested that creation of Water Users Associations (WUAs), envisaged under RIDF, would help in effective water distribution, maintenance and collection of water charges.Resource /Energy Economics and Policy,

Synthesis and Evaluation of Novel Biologically Active Compounds

SCP-1, a potent derivative of acetaminophen, exhibits significantly diminished hepatotoxicity and nephrotoxicity relative to acetaminophen and nitrate ester derivatives of acetaminophen. It was therefore of interest to explore the development of nitric oxide donor analogs of SCP-1 to identify compounds that could have enhanced analgesic and/or antipyretic activity while taking advantage of the very low liver and kidney toxicity inherent to SCP-1. In this project, a series of nitrate ester analogues of the SCP-1 were prepared as potential nitric oxide donors. The synthesis of SCP analogs was achieved by triflic acid catalyzed O-acylation of SCP-1 with chloroalkanoyl chlorides followed by nitration with silver nitrate. The chloroesters and corresponding nitrate esters were obtained in high yields (\u3e90%). Preliminary hepatotoxicity studies revealed the nitrate esters to be well tolerated by human hepatocytes and had little effect on the three cytochrome P450 enzymes tested (CYP3A4, CYP2E1 and CYP2D6). In addition, the nitrate esters exhibited antipyretic activity similar to acetaminophen. With the emerging interest in 3,3-diarylazetidines as novel motifs in drug discovery programs, an easy, efficient, scalable synthetic method that could accommodate the introduction of both electron-rich and electron-deficient aryl groups for preparation of diversely substituted 3,3-diarylazetidines would be valuable to medicinal chemists. In this second project, a versatile synthesis of 3,3-diaryl azetidines from N-Boc-3-aryl-3-azetidinols using Friedel-Crafts arylation conditions with AlCl3 is described. A series of substituted diaryl azetidines were readily prepared and isolated as the oxalate salts in high yield and high purity. The 3,3-diaryl azetidine oxalates were then easily converted into N-alkyl and N-acyl analogues in high overall yields (\u3e85%). In the last project, A general synthesis of pyruvate esters was developed. Using this method, a series of alkyl pyruvate esters were synthesized in moderate to high yields (56-93%). This was achieved in four steps starting from the readily available triethyl-2-phosphonopropionate which was converted to the alkene ethyl 2,3-dimethyl-2-butenoate using Horner-Wadsworth-Emmons reaction. The ethyl ester was hydrolyzed to the corresponding carboxylic acid after which a series of esters were prepared using Steglich esterification. The esters were then converted to their corresponding pyruvate esters via ozonolysis

Quantifying the urban forest environment using dense discrete return LiDAR and aerial color imagery for segmentation and object-level biomass assessment

The urban forest is becoming increasingly important in the contexts of urban green space and recreation, carbon sequestration and emission offsets, and socio-economic impacts. In addition to aesthetic value, these green spaces remove airborne pollutants, preserve natural resources, and mitigate adverse climate changes, among other benefits. A great deal of attention recently has been paid to urban forest management. However, the comprehensive monitoring of urban vegetation for carbon sequestration and storage is an under-explored research area. Such an assessment of carbon stores often requires information at the individual tree level, necessitating the proper masking of vegetation from the built environment, as well as delineation of individual tree crowns. As an alternative to expensive and time-consuming manual surveys, remote sensing can be used effectively in characterizing the urban vegetation and man-made objects. Many studies in this field have made use of aerial and multispectral/hyperspectral imagery over cities. The emergence of light detection and ranging (LiDAR) technology, however, has provided new impetus to the effort of extracting objects and characterizing their 3D attributes - LiDAR has been used successfully to model buildings and urban trees. However, challenges remain when using such structural information only, and researchers have investigated the use of fusion-based approaches that combine LiDAR and aerial imagery to extract objects, thereby allowing the complementary characteristics of the two modalities to be utilized. In this study, a fusion-based classification method was implemented between high spatial resolution aerial color (RGB) imagery and co-registered LiDAR point clouds to classify urban vegetation and buildings from other urban classes/cover types. Structural, as well as spectral features, were used in the classification method. These features included height, flatness, and the distribution of normal surface vectors from LiDAR data, along with a non-calibrated LiDAR-based vegetation index, derived from combining LiDAR intensity at 1064 nm with the red channel of the RGB imagery. This novel index was dubbed the LiDAR-infused difference vegetation index (LDVI). Classification results indicated good separation between buildings and vegetation, with an overall accuracy of 92% and a kappa statistic of 0.85. A multi-tiered delineation algorithm subsequently was developed to extract individual tree crowns from the identified tree clusters, followed by the application of species-independent biomass models based on LiDAR-derived tree attributes in regression analysis. These LiDAR-based biomass assessments were conducted for individual trees, as well as for clusters of trees, in cases where proper delineation of individual trees was impossible. The detection accuracy of the tree delineation algorithm was 70%. The LiDAR-derived biomass estimates were validated against allometry-based biomass estimates that were computed from field-measured tree data. It was found out that LiDAR-derived tree volume, area, and different distribution parameters of height (e.g., maximum height, mean of height) are important to model biomass. The best biomass model for the tree clusters and the individual trees showed an adjusted R-Squared value of 0.93 and 0.58, respectively. The results of this study showed that the developed fusion-based classification approach using LiDAR and aerial color (RGB) imagery is capable of producing good object detection accuracy. It was concluded that the LDVI can be used in vegetation detection and can act as a substitute for the normalized difference vegetation index (NDVI), when near-infrared multiband imagery is not available. Furthermore, the utility of LiDAR for characterizing the urban forest and associated biomass was proven. This work could have significant impact on the rapid and accurate assessment of urban green spaces and associated carbon monitoring and management