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4. Predictive Dirac neutrino spectrum with strong CP solution in SU(5)L × SU(5)R unification.

Author

Babu, K.S., Mohapatra, Rabindra N., and Thapa, Anil

Subjects
*NEUTRINOS, *PROTON decay, *GAUGE symmetries, *NEUTRINO mass, *FERMIONS, *AXIONS
Abstract

We develop a grand unified theory of matter and forces based on the gauge symmetry SU(5)L × SU(5)R with parity interchanging the two factor groups. Our main motivation for such a construction is to realize a minimal GUT embedding of left-right symmetric models that provide a parity solution to the strong CP problem without the axion. We show how the gauge couplings unify with an intermediate gauge symmetry SU(3)cL × SU(2)2L × U(1)L × SU(5)R, and establish its consistency with proton decay constraints. The model correctly reproduces the observed fermion masses and mixings and leads to naturally light Dirac neutrinos with their Yukawa couplings suppressed by a factor MI/MG, the ratio of the intermediate scale to the GUT scale. We call this mechanism type II-Dirac seesaw. Furthermore, the model predicts δCP = ±(130.4±1.2)° and = (4.8 – 8.4) meV for the Dirac CP phase and the lightest neutrino mass. We demonstrate how the model solves the strong CP problem via parity symmetry. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Contributors

Author

Al-Babili, S., primary, Babu, K.S., additional, Das, I.K., additional, Haussmann, B.I.G., additional, Kountche, B.A., additional, Mishra, J.S., additional, Nagaraja, A., additional, Padmaja, P.G., additional, Prasad, G.S., additional, Rajendrakumar, P., additional, and Rakshit, S., additional

Published
2016
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17. Optimal water distribution network design with honey-bee mating optimization

Author

Mohan, S. and Babu, K.S. Jinesh

Subjects
Mathematical optimization -- Research, Technology application, Computers, Engineering and manufacturing industries, Science and technology
Abstract

Water distribution network is a costly infrastructure and plays a crucial role in supplying water for the consumers especially for those who are living in the urban areas. The importance and huge capital cost of the system leads to considerable attention on seeking the optimal cost design. The necessity for such a sound research attention arises from the complexity associated with the problem. In the recent years, stochastic optimization algorithms like genetic algorithm, simulated annealing, ant colony optimization etc. are found to be successful in exploring the optimal combination of pipe diameters that can satisfy the hydraulic-head requirements with least cost. In this paper, the details on the optimal water distribution network design with a novel technique called honey-bee mating optimization and its validation with two benchmark water distribution networks are presented. From the results, it is observed that the proposed algorithm identifies the optimal solution with relatively less number of evaluations than the other well-established stochastic optimization algorithms. CE Database subject headings: Optimization; Algorithms; Stochastic models; Water distribution systems; Water supply. Author keywords: Optimization algorithms; Stochastic models; Water distribution systems; Water supply. DOI: 10.1061/(ASCE)CP/1943-5487.0000018

Published
2010
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18. Water distribution network design using heuristics-based algorithm

Author

Mohan, S. and Babu, K.S. Jinesh

Subjects
Mathematical optimization -- Analysis, Algorithms -- Analysis, Heuristic programming -- Design and construction, Algorithm, Computers, Engineering and manufacturing industries, Science and technology
Abstract

Water distribution network that includes supply reservoirs, overhead tanks, consumer demand nodes, interconnecting pipes, lifting pumps, and control valves is the main mode of water supply for majority of the communities especially in urban areas. Supply of required quantity of water and at right time is the primary objective of water distribution network analysis. The analysis of water distribution networks can be broadly classified into design and operation problems and both problems have been the focus of many researchers over the past three decades. In the water distribution network design problems, the target is attaining the cost effective configuration that satisfies the minimum hydraulic head requirement at the demand nodes. In this paper, a new algorithm for design of water distribution network namely 'heuristics-based algorithm' which completely utilizes the implicit information associated with the water distribution network to be designed has been proposed and validated with two water distribution networks. It is found that the proposed algorithm performs well for the least-cost design of water distribution networks. CE Database subject headings: Water distribution systems; Algorithms; Optimization; Network design; Water supply; Water pipelines.

Published
2009

20. Strategy for refinement of nodal densities and integration cells in EFG technique

Author

Bhavana S.S. Patel, Katta Venkataramana, and Babu K.S. Narayan

Subjects
Mathematical optimization, Computer science, Mechanical Engineering, Mode (statistics), Fracture mechanics, 02 engineering and technology, Building and Construction, Topology, 01 natural sciences, 010101 applied mathematics, 020303 mechanical engineering & transports, 0203 mechanical engineering, Mechanics of Materials, Convergence (routing), Meshfree methods, Node (circuits), 0101 mathematics, Galerkin method, Stress intensity factor, Civil and Structural Engineering, Stress concentration
Abstract

MeshFree methods have become popular owing to the ease with which high stress gradients can be identified and node density distribution can be reformulated to accomplish faster convergence. This paper presents a strategy for nodal density refinement with strain energy as basis in Element-Free Galerkin MeshFree technique. Two popular flat plate problems are considered for the demonstration of the proposed strategies. Issue of integration errors introduced during nodal density refinement have been addressed by suggesting integration cell refinement. High stress effects around two symmetrical semi-circular notches under in-plane axial load have been addressed in the first problem. The second considers crack propagation under mode I and mode II fracture loading by the way of introducing high stress intensity through line crack. The computational efficacy of the adaptive refinement strategies proposed has been highlighted.

Published
2016

22. Review of Particle Physics

Author

Eidelman, S., Hayes, K.G., Olive, K.A., Aguilar-Benitez, M., Amsler, C., Asner, D., Babu, K.S., Barnett, R.M., Beringer, J., Burchat, P.R., Carone, C.D., Caso, S., Conforto, G., Dahl, O., D'Ambrosio, G., Doser, M., Feng, J.L., Gherghetta, T., Gibbons, L., Goodman, M., Grab, C., Groom, D.E., Gurtu, A., Hagiwara, K., Hernández-Rey, J.J., Hikasa, K., Honscheid, K., Jawahery, H., Kolda, C., Kwon, Y., Mangano, M.L., Manohar, A.V., March-Russell, J., Masoni, A., Miquel, R., Mönig, K., Murayama, H., Nakamura, K., Navas, S., Pape, L., Patrignani, C., Piepke, A., Raffelt, G., Roos, M., Tanabashi, M., Terning, J., Törnqvist, N.A., Trippe, T.G., Vogel, P., Wohl, C.G., Workman, R.L., Yao, W.-M., Zyla, P.A., Armstrong, B., Gee, P.S., Harper, G., Lugovsky, K.S., Lugovsky, S.B., Lugovsky, V.S., Rom, A., Artuso, M., Barberio, E., Battaglia, M., Bichsel, H., Biebel, O., Bloch, P., Cahn, R.N., Casper, D., Cattai, A., Chivukula, R.S., Cowan, G., Damour, T., Desler, K., Dobbs, M.A., Drees, M., Edwards, A., Edwards, D.A., Elvira, V.D., Erler, J., Ezhela, V.V., Fetscher, W., Fields, B.D., Foster, B., Froidevaux, D., Fukugita, M., Gaisser, T.K., Garren, L., Gerber, H.-J., Gerbier, G., Gilman, F.J., Haber, H.E., Hagmann, C., Hewett, J., Hinchliffe, I., Hogan, C.J., Höhler, G., Igo-Kemenes, P., Jackson, J.D., Johnson, K.F., Karlen, D., Kayser, B., Kirkby, D., Klein, S.R., Kleinknecht, K., Knowles, I.G., Kreitz, P., Kuyanov, Yu.V., Lahav, O., Langacker, P., Liddle, A., Littenberg, L., Manley, D.M., Martin, A.D., Narain, M., Nason, P., Nir, Y., Peacock, J.A., Quinn, H.R., Raby, S., Ratcliff, B.N., Razuvaev, E.A., Renk, B., Rolandi, G., Ronan, M.T., Rosenberg, L.J., Sachrajda, C.T., Sakai, Y., Sanda, A.I., Sarkar, S., Schmitt, M., Schneider, O., Scott, D., Seligman, W.G., Shaevitz, M.H., Sjöstrand, T., Smoot, G.F., Spanier, S., Spieler, H., Spooner, N.J.C., Srednicki, M., Stahl, A., Stanev, T., Suzuki, M., Tkachenko, N.P., Trilling, G.H., Valencia, G., van Bibber, K., Vincter, M.G., Ward, D.R., Webber, B.R., Whalley, M., Wolfenstein, L., Womersley, J., Woody, C.L., Zenin, O.V., and Zhu, R.-Y.

Published
2004
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23. Gauge & Higgs boson summary table

Author

Eidelman, S., Hayes, K.G., Olive, K.A., Aguilar-Benitez, M., Amsler, C., Asner, D., Babu, K.S., Barnett, R.M., Beringer, J., Burchat, P.R., Carone, C.D., Caso, C., Conforto, G., Dahl, O., D'Ambrosio, G., Doser, M., Feng, J.L., Gherghetta, T., Gibbons, L., Goodman, M., Grab, C., Groom, D.E., Gurtu, A., Hagiwara, K., Hernández-Rey, J.J., Hikasa, K., Honscheid, K., Jawahery, H., Kolda, C., Kwon, Y., Mangano, M.L., Manohar, A.V., March-Russell, J., Masoni, A., Miquel, R., Mönig, K., Murayama, H., Nakamura, K., Navas, S., Pape, L., Patrignani, C., Piepke, A., Raffelt, G., Roos, M., Tanabashi, M., Terning, J., Törnqvist, N.A., Trippe, T.G., Vogel, P., Wohl, C.G., Workman, R.L., Yao, W.-M., Zyla, P.A., Armstrong, B., Gee, P.S., Harper, G., Lugovsky, K.S., Lugovsky, S.B., Lugovsky, V.S., Rom, A., Artuso, M., Barberio, E., Battaglia, M., Bichsel, H., Biebel, O., Bloch, P., Cahn, R.N., Casper, D., Cattai, A., Chivukula, R.S., Cowan, G., Damour, T., Desler, K., Dobbs, M.A., Drees, M., Edwards, A., Edwards, D.A., Elvira, V.D., Erler, J., Ezhela, V.V., Fetscher, W., Fields, B.D., Foster, B., Froidevaux, D., Fukugita, M., Gaisser, T.K., Garren, L., Gerber, H.-J., Gerbier, G., Gilman, F.J., Haber, H.E., Hagmann, C., Hewett, J., Hinchliffe, I., Hogan, C.J., Höhler, G., Igo-Kemenes, P., Jackson, J.D., Johnson, K.F., Karlen, D., Kayser, B., Kirkby, D., Klein, S.R., Kleinknecht, K., Knowles, I.G., Kreitz, P., Kuyanov, Yu.V., Lahav, O., Langacker, P., Liddle, A., Littenberg, L., Manley, D.M., Martin, A.D., Narain, M., Nason, P., Nir, Y., Peacock, J.A., Quinn, H.R., Raby, S., Ratcliff, B.N., Razuvaev, E.A., Renk, B., Rolandi, G., Ronan, M.T., Rosenberg, L.J., Sachrajda, C.T., Sakai, Y., Sanda, A.I., Sarkar, S., Schmitt, M., Schneider, O., Scott, D., Seligman, W.G., Shaevitz, M.H., Sjöstrand, T., Smoot, G.F., Spanier, S., Spieler, H., Spooner, N.J.C., Srednicki, M., Stahl, A., Stanev, T., Suzuki, M., Tkachenko, N.P., Trilling, G.H., Valencia, G., van Bibber, K., Vincter, M.G., Ward, D.R., Webber, B.R., Whalley, M., Wolfenstein, L., Womersley, J., Woody, C.L., Zenin, O.V., and Zhu, R.-Y.

Published
2004
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28. Multiple Diseases, Insect Pests Resistant Genotypes and Their Utilization in Breeding for Resistance in Wheat and Triticale

Author

Babu K.S, Nagarajan S, Sharma Indu, Sharma A.K, and Singh D.P

Subjects
Loose smut, biology, Triticum aestivum, Triticale, Multiple disease and insect pests, Plant disease resistance, biology.organism_classification, Karnal bunt, resistant genotypes, Agronomy, Resistance breeding, Smut, Blight, T. durum, T. dicoccum, Cultivar, Powdery mildew
Abstract

A total of 347 numbers of genotypes ofTriticum aestivum, 66 ofT. durum, 8 ofT. dicoccumand 18 of triticale possessing resistance against multiple diseases and insect pests resistance were taken for the study. These were identified resistant to biotic stressesthrough rigorous evaluation under artificially inoculated conditions at hot spot locations in six agro ecological zones of India during 1998-99 till 2011-12 cropping seasons. The diseases and insect pests targeted were three rusts (stem, leaf and stripe rust), Karnal bunt, flag smut, leaf blight, powdery mildew, loose smut, brown wheat mite, root aphid, foliar aphid and shoot fly. The seeds of these genotypes along with passport data on disease resistance were shared with breeders at 30 main wheat and triticale breeding centres in India. The percentage of centres utilized these genotypes for hybridization and resistance breeding ranged from 4.0-63.6%. The per cent utilization was maximum in case ofT. aestivumfollowed byT. durum, T. dicoccum. The most preferred genotypes ofT. aestivumwere, ‘DBW 18’, ‘DBW 32’, ‘GW 276’, ‘HD 2851’, ‘HD 2964’, ‘HD 2997’, ‘HP 1872’, ‘HW 2044’, ‘HW 3027’, ‘HPW 42’, ‘HPW 155’, ‘HPW 237’, ‘HPW 285’, ‘HUW 620’, ‘HS 295’, ‘HS 318’, ‘HS 345’, ‘HS 375’, ‘HS 420’, ‘HS 468’, ‘HS 493’, ‘HW 2045’, ‘HW 3083’, ‘HW 5037’, ‘HW 5208’, ‘K 9351’, ‘K 9441’, ‘MACS 295’, ‘MACS 2959’, ‘NW 3087’, ‘NW 1012’, ‘PBW 373’, ‘PBW 475’, ‘PBW 521’, ‘PBW 550’, ‘PBW 554’, ‘PBW 573’, ‘PBW 589’, ‘Raj 3765’, ‘Raj 4012’, ‘RAJ 4120’, ‘RAJ 4131’, ‘UP 2425’, ‘UP 2719’, ‘VL 801’, ‘VL 868’ and ‘VL 907’. In case ofT. durum,66 genotypes were utilized by 4.0-36% centres and most liked were, ‘AKDW 4155’, ‘CDW 04’, ‘GW 1139’, ‘HD 4696’, ‘HI 8498’, ‘MACS 3313’, ‘PDW 267’ and ‘PDW 312’. Likewise, out of eight genotypes ofT. dicoccum, ‘MACS 2956’ (32.0%) and ‘MACS 2971’ (15.0%) were used most. Utilization of 18 numbers of triticale genotypes was 4.0-14.8% only. It may be due to lesser preference of triticale as compared to bread and durum wheat for breeding. The major preference of breeders was on genotypes having resistance against three or two rusts depending on agro climatic zones. The genotypes havingLr34gene which is known for providing resistance to leaf rust were also found to be resistant to other diseases and aphids. The incorporation of resistance genes from resistant genotypes shared in breeding programme has helped greatly in management of diseases and insect pests using host resistance and avoided or reduced application of costly fungicides on wheat and producing pesticide free wheat in India. The deployment of resistant cultivars strategically in areas of prevalence of diseases and insect pests helped to further curtail losses in yield and quality of wheat and outbreak of rusts and other diseases thus ensure food self sufficiency as well as export of surplus wheat in future. These genotypes will be good source for molecular studies related to multiple disease and insect pests.

Published
2014

30. Theory of Neutrinos: a White Paper

Author

Mohapatra, R.N., primary, Antusch, S., additional, Babu, K.S., additional, Barenboim, G., additional, Chen, Mu-Chun, additional, Davidson, S., additional, de Gouvea, A., additional, de Holanda, P., additional, Dutta, Bhaskar, additional, Grossman, Y., additional, Joshipura, A., additional, Kayser, B., additional, Kersten, J., additional, Keum, Y.Y., additional, King, S.F., additional, Langacker, P., additional, Lindner, M., additional, Loinaz, W., additional, Masina, I., additional, Mocioiu, I., additional, and Mohanty, S., additional

Published
2006
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31. Theory of neutrinos: A White paper

Author

Mohapatra, R.N., primary, Antusch, S., additional, Babu, K.S., additional, Barenboim, G., additional, Chen, Mu-Chun, additional, Davidson, S., additional, de Gouvea, A., additional, de Holanda, P., additional, Dutta, Bhaskar, additional, Grossman, Y., additional, Joshipura, A., additional, Kayser, B., additional, Kersten, J., additional, Keum, Y.Y., additional, King, S.F., additional, Langacker, P., additional, Lindner, M., additional, Loinaz, W., additional, Masina, I., additional, Mocioiu, I., additional, and Mohanty, S., additional

Published
2005
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41. Fundamental Physics at the Intensity Frontier

Author

Hewett, J.L., Weerts, H., Brock, R., Butler, J.N., Casey, B.C.K., Collar, J., de Gouvea, A., Essig, R., Grossman, Y., Haxton, W., Jaros, J.A., Jung, C.K., Lu, Z.T., Pitts, K., Ligeti, Z., Patterson, J.R., Ramsey-Musolf, M., Ritchie, J.L., Roodman, A., Scholberg, K., Wagner, C.E.M., Zeller, G.P., Aefsky, S., Afanasev, A., Agashe, K., Albright, C., Alonso, J., Ankenbrandt, C., Aoki, M., Arguelles, C.A., Arkani-Hamed, N., Armendariz, J.R., Armendariz-Picon, C., Arrieta Diaz, E., Asaadi, J., Asner, D.M., Babu, K.S., Bailey, K., Baker, O., Balantekin, B., Baller, B., Bass, M., Batell, B., Beacham, J., Behr, J., Berger, N., Bergevin, M., Berman, E., Bernstein, R., Bevan, A.J., Bishai, M., Blanke, M., Blessing, S., Blondel, A., Blum, T., Bock, G., Bodek, A., Bonvicini, G., Bossi, F., Boyce, J., Breedon, R., Breidenbach, M., Brice, S.J., Briere, R.A., Brodsky, S., Bromberg, C., Bross, A., Browder, T.E., Bryman, D.A., Buckley, M., Burnstein, R., Caden, E., Campana, P., Carlini, R., Carosi, G., Castromonte, C., Cenci, R., Chakaberia, I., Chen, Mu-Chun, Cheng, C.H., Choudhary, B., Christ, N.H., Christensen, E., Christy, M.E., Chupp, T.E., Church, E., Cline, D.B., Coan, T.E., Coloma, P., Comfort, J., Coney, L., Cooper, J., Cooper, R.J., Cowan, R., Cowen, D.F., Cronin-Hennessy, D., Datta, A., Davies, G.S., Demarteau, M., DeMille, D.P., Denig, A., Dermisek, R., Deshpande, A., Dewey, M.S., Dharmapalan, R., Dhooghe, J., Dietrich, M.R., Diwan, M., Djurcic, Z., Dobbs, S., Duraisamy, M., Dutta, Bhaskar, Duyang, H., Dwyer, D.A., Eads, M., Echenard, B., Elliott, S.R., Escobar, C., Fajans, J., Farooq, S., Faroughy, C., Fast, J.E., Feinberg, B., Felde, J., Feldman, G., Fierlinger, P., Fileviez Perez, P., Filippone, B., Fisher, P., Fleming, B.T., Flood, K.T., Forty, R., Frank, M.J., Freyberger, A., Friedland, A., Gandhi, R., Ganezer, K.S., Garcia, A., Garcia, F.G., Gardner, S., Garrison, L., Gasparian, A., Geer, S., Gehman, V.M., Gershon, T., Gilchriese, M., Ginsberg, C., Gogoladze, I., Gonderinger, M., Goodman, M., Gould, H., Graham, M., Graham, P.W., Gran, R., Grange, J., Gratta, G., Green, J.P., Greenlee, H., Group, R.C., Guardincerri, E., Gudkov, V., Guenette, R., Haas, A., Hahn, A., Han, T., Handler, T., Hardy, J.C., Harnik, R., Harris, D.A., Harris, F.A., Harris, P.G., Hartnett, J., He, B., Heckel, B.R., Heeger, K.M., Henderson, S., Hertzog, D., Hill, R., Hinds, E.A., Hitlin, D.G., Holt, R.J., Holtkamp, N., Horton-Smith, G., Huber, P., Huelsnitz, W., Imber, J., Irastorza, I., Jaeckel, J., Jaegle, I., James, C., Jawahery, A., Jensen, D., Jessop, C.P., Jones, B., Jostlein, H., Junk, T., Kagan, A.L., Kalita, M., Kamyshkov, Y., Kaplan, D.M., Karagiorgi, G., Karle, A., Katori, T., Kayser, B., Kephart, R., Kettell, S., Kim, Y.K., Kirby, M., Kirch, K., Klein, J., Kneller, J., Kobach, A., Kohl, M., Kopp, J., Kordosky, M., Korsch, W., Kourbanis, I., Krisch, A.D., Krizan, P., Kronfeld, A.S., Kulkarni, S., Kumar, K.S., Kuno, Y., Kutter, T., Lachenmaier, T., Lamm, M., Lancaster, J., Lancaster, M., Lane, C., Lang, K., Langacker, P., Lazarevic, S., Le, T., Lee, K., Lesko, K.T., Li, Y., Lindgren, M., Lindner, A., Link, J., Lissauer, D., Littenberg, L.S., Littlejohn, B., Liu, C.Y., Loinaz, W., Lorenzon, W., Louis, W.C., Lozier, J., Ludovici, L., Lueking, L., Lunardini, C., MacFarlane, D.B., Machado, P.A.N., Mackenzie, P.B., Maloney, J., Marciano, W.J., Marsh, W., Marshak, M., Martin, J.W., Mauger, C., McFarland, K.S., McGrew, C., McLaughlin, G., McKeen, D., McKeown, R., Meadows, B.T., Mehdiyev, R., Melconian, D., Merkel, H., Messier, M., Miller, J.P., Mills, G., Minamisono, U.K., Mishra, S.R., Mocioiu, I., Sher, S.Moed, Mohapatra, R.N., Monreal, B., Moore, C.D., Morfin, J.G., Mousseau, J., Moustakas, L.A., Mueller, G., Mueller, P., Muether, M., Mumm, H.P., Munger, C., Murayama, H., Nath, P., Naviliat-Cuncin, O., Nelson, J.K., Neuffer, D., Nico, J.S., Norman, A., Nygren, D., Obayashi, Y., O'Connor, T.P., Okada, Y., Olsen, J., Orozco, L., Orrell, J.L., Osta, J., Pahlka, B., Paley, J., Papadimitriou, V., Papucci, M., Parke, S., Parker, R.H., Parsa, Z., Partyka, K., Patch, A., Pati, J.C., Patterson, R.B., Pavlovic, Z., Paz, Gil, Perdue, G.N., Perevalov, D., Perez, G., Petti, R., Pettus, W., Piepke, A., Pivovaroff, M., Plunkett, R., Polly, C.C., Pospelov, M., Povey, R., Prakesh, A., Purohit, M.V., Raby, S., Raaf, J.L., Rajendran, R., Rajendran, S., Rameika, G., Ramsey, R., Rashed, A., Ratcliff, B.N., Rebel, B., Redondo, J., Reimer, P., Reitzner, D., Ringer, F., Ringwald, A., Riordan, S., Roberts, B.L., Roberts, D.A., Robertson, R., Robicheaux, F., Rominsky, M., Roser, R., Rosner, J.L., Rott, C., Rubin, P., Saito, N., Sanchez, M., Sarkar, S., Schellman, H., Schmidt, B., Schmitt, M., Schmitz, D.W., Schneps, J., Schopper, A., Schuster, P., Schwartz, A.J., Schwarz, M., Seeman, J., Semertzidis, Y.K., Seth, K.K., Shafi, Q., Shanahan, P., Sharma, R., Sharpe, S.R., Shiozawa, M., Shiltsev, V., Sigurdson, K., Sikivie, P., Singh, J., Sivers, D., Skwarnicki, T., Smith, N., Sobczyk, J., Sobel, H., Soderberg, M., Song, Y.H., Soni, A., Souder, P., Sousa, A., Spitz, J., Stancari, M., Stavenga, G.C., Steffen, J.H., Stepanyan, S., Stoeckinger, D., Stone, S., Strait, J., Strassler, M., Sulai, I.A., Sundrum, R., Svoboda, R., Szczerbinska, B., Szelc, A., Takeuchi, T., Tanedo, P., Taneja, S., Tang, J., Tanner, D.B., Tayloe, R., Taylor, I., Thomas, J., Thorn, C., Tian, X., Tice, B.G., Tobar, M., Tolich, N., Toro, N., Towner, I.S., Tsai, Y., Tschirhart, R., Tunnell, C.D., Tzanov, M., Upadhye, A., Urheim, J., Vahsen, S., Vainshtein, A., Valencia, E., Van de Water, R.G., Van de Water, R.S., Velasco, M., Vogel, J., Vogel, P., Vogelsang, W., Wah, Y.W., Walker, D., Weiner, N., Weltman, A., Wendell, R., Wester, W., Wetstein, M., White, C., Whitehead, L., Whitmore, J., Widmann, E., Wiedemann, G., Wilkerson, J., Wilkinson, G., Wilson, P., Wilson, R.J., Winter, W., Wise, M.B., Wodin, J., Wojcicki, S., Wojtsekhowski, B., Wongjirad, T., Worcester, E., Wurtele, J., Xin, T., Xu, J., Yamanaka, T., Yamazaki, Y., Yavin, I., Yeck, J., Yeh, M., Yokoyama, M., Yoo, J., Young, A., Zimmerman, E., Zioutas, K., Zisman, M., Zupan, J., and Zwaska, R.

Subjects
Nuclear Theory, High Energy Physics::Phenomenology, High Energy Physics::Experiment, Nuclear Experiment, Particle Physics - Experiment
Abstract

The Proceedings of the 2011 workshop on Fundamental Physics at the Intensity Frontier. Science opportunities at the intensity frontier are identified and described in the areas of heavy quarks, charged leptons, neutrinos, proton decay, new light weakly-coupled particles, and nucleons, nuclei, and atoms. The Proceedings of the 2011 workshop on Fundamental Physics at the Intensity Frontier. Science opportunities at the intensity frontier are identified and described in the areas of heavy quarks, charged leptons, neutrinos, proton decay, new light weakly-coupled particles, and nucleons, nuclei, and atoms.

Published
2012

44. Biological evaluation of 3-hydroxybenzyl alcohol, an extrolite produced by Aspergillus nidulans strain KZR-132.

Author

Kumar, C. Ganesh, Mongolla, P., Pombala, S., Bandi, S., Babu, K.S., and Ramakrishna, K.V.S.

Subjects
BIOACTIVE compounds, BENZYL alcohol, ASPERGILLUS nidulans, CHEMICAL structure, ANTI-infective agents
Abstract

Aims The aim of the study was to purify and characterize a bioactive compound from Aspergillus nidulans strain KZR-132 and its biological evaluation. Methods and Results A bioactive extolite was purified from A. nidulans strain KZR-132, and its chemical structure was elucidated as 3-hydroxylbenzyl alcohol (3- HBA) based on 1H and 13C NMR, FT- IR and mass spectroscopic analysis. The antimicrobial efficacy of 3- HBA was established against Gram-positive, Gram-negative bacteria and different Candida strains. It also showed promising antibiofilm activity against various tested microbial strains. Reactive oxygen species induced by 3- HBA treatment on different Candida strains killed most of the cells and showed necrotic effect. It also exhibited dose-dependent antioxidant and anti-inflammatory activities. Conclusions This bioactive extrolite produced by A. nidulans isolated from a niche habitat was demonstrated to possess significant biotechnological and pharmacological potential since it exhibited broad-spectrum antimicrobial and antibiofilm activities which are reported for the first time. Significance and Impact of the Study The overall study demonstrates that 3- HBA produced by A. nidulans KZR-132 is a promising bioactive metabolite and possibly can function as a pharmacologically suitable broad-spectrum antimicrobial drug candidate against various dreaded human-related bacterial and fungal pathogens. [ABSTRACT FROM AUTHOR]

Published
2017
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45. Segmentation of Diabetic Wound by Multidimensional Clustering for Quantitative Assessment of Healing Process

Author

Babu, K.S., Subudhi, Asit, and Sabut, Sukanta

Abstract

Background: Periodically assessment of the healing process of diabetic wound is a very important task for clinicians. The quantitative analysis of wound is useful to monitor and evaluate the healing process with the intervention of drug therapies. Currently, the evaluation process focuses mainly on visual inspection, which is not accurate enough to accomplish the task. Methods: Segmentation and detection of region of the wound in tissues is an emerging field for assessing the healing process. This paper presents the supervised learning methods to detect and classify the type of wound tissues. Fast Fuzzy C-means and K-means clustering algorithms has been implemented for classifying and detecting the boundary of wounds and also the size of the wound has been measured from images. Results: The intensity of the images has been normalized, and wounds were segmented in five images collected from the open source database. The output result shows that the boundary of the wound has been extracted accurately by both the methods. The enhanced Fast Fuzzy C-means provides better visual segmented output compared K-means process in terms of high PSNR and low MSE values. The high PSNR of 55.57 is measured in EnFuzzy C-means compared to K-means algorithm with a value of 54.74 and the effectiveness of the process has also been calculated by integrating both the process. Conclusion: These methods may be useful in accessing and analyzing the wound healing process in qualitative and quantitative manner in diabetic cases.

Published
2018

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