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1. Machine learning hybrid approach for the prediction of surface tension profiles of hydrocarbon surfactants in aqueous solution

Author

Seddon, D, Müller, EA, Cabral, JT, Procter & Gamble Technical Centres Ltd, Royal Academy Of Engineering, and Engineering & Physical Science Research Council (E

Subjects
Chemical Physics, 02 Physical Sciences, Water, 09 Engineering, Hydrocarbons, Surfaces, Coatings and Films, Electronic, Optical and Magnetic Materials, Machine Learning, Biomaterials, Surface-Active Agents, Colloid and Surface Chemistry, QSPR, Surfactant, Surface Tension, 03 Chemical Sciences, Micelles, Critical micelle concentration
Abstract

HYPOTHESIS: Predicting the surface tension (SFT)-log(c) profiles of hydrocarbon surfactants in aqueous solution is computationally non-trivial, and empirically challenging due to the diverse and complex architecture and interactions of surfactant molecules. Machine learning (ML), combining a data-based and knowledge-based approach, can provide a powerful means to relate molecular descriptors to SFT profiles. EXPERIMENTS: A dataset of SFT for 154 model hydrocarbon surfactants at 20-30 °C is fitted to the Szyszkowski equation to extract three characteristic parameters (Γmax,KL and critical micelle concentration (CMC)) which are correlated to a series of 2D and 3D molecular descriptors. Key (∼10) descriptors were selected by removing co-correlation, and employing a gradient-boosted regressor model to rank feature importance and carry out recursive feature elimination (RFE). The hyperparameters of each target-variable model were fine-tuned using a randomised cross-validated grid search, to improve predictive ability and reduce overfitting. FINDINGS: The ML models correlate favourably with test experimental data, with R2= 0.69-0.87, and the merits and limitations of the approach are discussed based on 'unseen' hydrocarbon surfactants. The incorporation of a knowledge-based framework provides an appropriate smoothing of the experimental data which simplifies the data-driven approach and enhances its generality. Open-source codes and a brief tutorial are provided.

Published
2022

2. The ALPHA antihydrogen trapping apparatus

Author

Amole, C, Andresen, GB, Ashkezari, MD, Baquero-Ruiz, M, Bertsche, W, Bowe, PD, Butler, E, Capra, A, Carpenter, PT, Cesar, CL, Chapman, S, Charlton, M, Deller, A, Eriksson, S, Escallier, J, Fajans, J, Friesen, T, Fujiwara, MC, Gill, DR, Gutierrez, A, Hangst, JS, Hardy, WN, Hayano, RS, Hayden, ME, Humphries, AJ, Hurt, JL, Hydomako, R, Isaac, CA, Jenkins, MJ, Jonsell, S, Jørgensen, LV, Kerrigan, SJ, Kurchaninov, L, Madsen, N, Marone, A, McKenna, JTK, Menary, S, Nolan, P, Olchanski, K, Olin, A, Parker, B, Povilus, A, Pusa, P, Robicheaux, F, Sarid, E, Seddon, D, Nasr, S Seif El, Silveira, DM, So, C, Storey, JW, Thompson, RI, Thornhill, J, Wells, D, van der Werf, DP, Wurtele, JS, Yamazaki, Y, and Collaboration, ALPHA

Subjects
Condensed Matter::Quantum Gases, Neutral atom trap, Molecular, Antiprotons, Atomic, Nuclear & Particles Physics, Other Physical Sciences, Positrons, Particle and Plasma Physics, Physics::Atomic and Molecular Clusters, Nuclear, Physics::Atomic Physics, Silicon Vertex Detector, Microwaves, Antihydrogen, Astronomical and Space Sciences
Abstract

The ALPHA collaboration, based at CERN, has recently succeeded in confining cold antihydrogen atoms in a magnetic minimum neutral atom trap and has performed the first study of a resonant transition of the anti-atoms. The ALPHA apparatus will be described herein, with emphasis on the structural aspects, diagnostic methods and techniques that have enabled antihydrogen trapping and experimentation to be achieved. © 2013 Elsevier B.V.

Published
2014

3. Population, labour and poverty project: population and poverty in Nepal

Author

Seddon D

Subjects
WEP pub, population growth, poverty, Nepal, food production, social class, land ownership, population, trend, population density, land utilization, deforestation, living conditions, calorie deficiency, social status, caste, sex discrimination, obstacle, basic needs, development policy, bibliography, graph, statistical table, pub PME, croissance démographique, pauvreté, Népal, pub PME, crecimiento demográfico, pobreza, Nepal, production alimentaire, classe sociale, propriété foncière, population, tendance, densité de population, utilisation des terres, déboisement, conditions de vie, déficience calorique, statut social, caste, discrimination fondée sur le sexe, obstacle, besoins essentiels, politique de développement, bibliographie, graphique, tableau statistique, producción alimentaria, clase social, propiedad de la tierra, población, tendencia, densidad de población, utilización de la tierra, deforestación, condiciones de vida, deficiencia calórica, condición social, casta, discriminación por razones de sexo, obstáculo, necesidades esenciales, política de desarrollo, bibliografía, gráfico, cuadros estadísticos
Abstract

ILO pub-WEP pub. Working paper on the relationship between population growth and poverty in Nepal - discusses food production, social class, land ownership and population trends; considers population density and its impact on land utilization and deforestation; examines living conditions, calorie deficiencys, social status disparities due to caste and sex discrimination, obstacles to the provision of basic needs, development policy, etc. Bibliography, graphs, statistical tables.

Published
1985

5. Magnesium for acute stroke (Intravenous Magnesium Efficacy in Stroke trial): randomised controlled trial

Author

Lees, K. R., Muir, K. W., Ford, I., Reid, J. L., Mendelow, A. D., Sandercock, P. A. G., Bath, P. M. W., Chen, C., Davis, S. M., Phillips, S. J., Saver, J., Vanhooren, G., Forbes, C., Murray, G., Bone, I., Norrie, J., Kean, S., Robertson, M., Murray, H., Mcilvenna, Y., Gardner, A., Bradford, A., Fenton, J., Sakhri, A., Rodger, M., Sanmuganathan, P., Milia, P., Chong, V., Teasdale, E., Davis, S., Donnan, G., Crimmins, D., Hankey, G., Phillips, S., Shuaib, A., Bailey, P., Jaramillo, A., Lisheng, L., Li, K. B., Jiang, X. D., Gao, B., Jia, Q. S., Cai, Z. L., Zhang, J. P., Feng, H. L., Xu, C. L., Zhang, Q., Ma, C., Zhang, H. Y., Wang, A. H., Yu, S. L., Cao, Y. B., Wang, X. H., Li, Y. W., Yuan, X. D., Meng, L. H., Li, L., Zhang, L. H., He, Y. J., Zhang, X. J., Ji, H., Wang, J. L., Li, Y. H., Cenek, M., Vlachova, I., Cheung, R., Gallai, V., Parnetti, L., Haur, L. S., Alvaro, L. C., Ozdemir, G., Nandi, K., Barrett, J., Sangster, G., Ford, G., Mcleod, M. J., Dijkhuizen, R., Grant, R., Adams, K., Wani, M., Steven, M., Srivastava, P. K., Bland, R., Curless, R., Evans, M., Murphy, P., Bruce, D., Jenkinson, D., Sharma, A., Power, M., Scane, A., Bishop-Miller, J., Roffe, C., Sleight, P., Deering, A., Kalra, L., Bath, P., Fulcher, R. A., Chaudhury, M. D., Ardron, M., Richard Lindley, Chadha, D. K., Hussain, R., Kelly, J., Villar, T., Athulathmudali, C., Seddon, D., Dewar, R. I., Watt, M., Kemp, T., Robinson, T., Sharma, J., Hudson, C., Erwin, L., Ali, M. S., Forsyth, D., Farag, R., Ross, I., Tsang, P., Kafetz, K., Tyrell, P., Ghosh, S. K., Patterson, J., Fricker, R., Kidwell, C., Neff, S., Friday, G., Mattio, T., Hwang, T. L., Simon, L., Burke, J., and Images Study Investigators

7. β-decay studies of r-process nuclei using the Advanced Implantation Detector Array (AIDA)

Author

Griffin, C. J., Davinson, T., Estrade, A., Braga, D., Burrows, I., Coleman-Smith, P., Grahn, T., Grant, A., Harkness-Brennan, L. J., Kogimtzis, M., Lazarus, I., Letts, S., Liu, Z., Lorusso, G., Matsui, K., Nishimura, S., Page, R. D., Prydderch, M., Pucknell, V., Sami Rinta-Antila, Roberts, O., Seddon, D. A., Simpson, J., Strachan, J., Thomas, S. L., and Woods, P. J.

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