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1,115 results on '"Ajani, P. A."'

1. Completing partial $k$-star designs

Author

Gunasekara, Ajani De Vas and Horsley, Daniel

Subjects
Mathematics - Combinatorics, 05C51
Abstract

A $k$-star is a complete bipartite graph $K_{1,k}$. A partial $k$-star design of order $n$ is a pair $(V,\mathcal{A})$ where $V$ is a set of $n$ vertices and $\mathcal{A}$ is a set of edge-disjoint $k$-stars whose vertex sets are subsets of $V$. If each edge of the complete graph with vertex set $V$ is in some star in $\mathcal{A}$, then $(V,\mathcal{A})$ is a (complete) $k$-star design. We say that $(V,\mathcal{A})$ is completable if there is a $k$-star design $(V,\mathcal{B})$ such that $\mathcal{A} \subseteq \mathcal{B}$. In this paper we determine, for all $k$ and $n$, the minimum number of stars in an uncompletable partial $k$-star design of order $n$., Comment: 16 pages, 0 figures

Published
2024

2. Teachers' Competencies in Digital Integration of Learning Contents in Dynamic Classroom Practices: A Review of Teacher Professional Development Needs

Author

Oluwatoyin Ayodele Ajani

Abstract

Introduction: Integrating digital tools and resources into classroom instruction has become increasingly essential in modern education. As technology advances, teachers face the challenge of effectively integrating digital learning content into dynamic classroom practices. This paper explores the competencies teachers require for this task, aiming to contribute to understanding teacher professional development needs in digital integration. Purpose: This study aims to investigate the competencies required by teachers for the successful integration of digital tools and resources into classroom practices. Methods: A comprehensive literature review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) diagram flow to address this aim. A total of 84 articles published from 2000 to 2024 were systematically reviewed, focusing on publications in English that addressed the professional development of teachers, technology integration into classroom practices, and digital competencies. Articles that did not meet these criteria were excluded from the analysis. Results: The synthesis of findings from the literature review highlighted the knowledge base of teachers' professional development needs in digital integration. The review identified critical competencies for successful digital integration, including technological proficiency, pedagogical knowledge, and content expertise. Additionally, theoretical frameworks such as Technological Pedagogical Content Knowledge (TPACK) and the SAMR model guided the exploration of teachers' competencies and their implications for instructional practices. Discussion: The implications of the study's findings extend to educational policy, teacher training programs, and classroom practices. By identifying critical competencies for successful digital integration, this study provides insights into areas for further research and teacher professional development. Moreover, the discussion delves into how these findings can inform the design of effective teacher training programs and support the development of pedagogical practices that leverage digital tools to enhance student learning outcomes. Limitations: Despite the thoroughness of the literature review process, it is essential to acknowledge certain limitations. The study focused primarily on articles published in English, potentially excluding relevant research published in other languages. Additionally, while the PRISMA diagram flow facilitated a systematic review, some relevant articles may need to be noticed. Conclusions: In conclusion, this study contributes to understanding teacher competencies required for effective digital integration of learning contents in dynamic classroom practices. The study identifies critical competencies and highlights areas for further research and teacher professional development by synthesising findings from relevant empirical studies and theoretical contributions. Ultimately, the findings have implications for educational policy, teacher training programs, and instructional practices to enhance student learning outcomes in the digital age.

Published
2024
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3. SAT and Lattice Reduction for Integer Factorization

Author

Ajani, Yameen and Bright, Curtis

Subjects
Computer Science - Cryptography and Security, Computer Science - Discrete Mathematics, Computer Science - Logic in Computer Science, Computer Science - Symbolic Computation
Abstract

The difficulty of factoring large integers into primes is the basis for cryptosystems such as RSA. Due to the widespread popularity of RSA, there have been many proposed attacks on the factorization problem such as side-channel attacks where some bits of the prime factors are available. When enough bits of the prime factors are known, two methods that are effective at solving the factorization problem are satisfiability (SAT) solvers and Coppersmith's method. The SAT approach reduces the factorization problem to a Boolean satisfiability problem, while Coppersmith's approach uses lattice basis reduction. Both methods have their advantages, but they also have their limitations: Coppersmith's method does not apply when the known bit positions are randomized, while SAT-based methods can take advantage of known bits in arbitrary locations, but have no knowledge of the algebraic structure exploited by Coppersmith's method. In this paper we describe a new hybrid SAT and computer algebra approach to efficiently solve random leaked-bit factorization problems. Specifically, Coppersmith's method is invoked by a SAT solver to determine whether a partial bit assignment can be extended to a complete assignment. Our hybrid implementation solves random leaked-bit factorization problems significantly faster than either a pure SAT or pure computer algebra approach., Comment: To appear in the 2024 Proceedings of the International Symposium on Symbolic and Algebraic Computation

Published
2024
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6. mRNA vaccine design for Epstein–Barr virus: an immunoinformatic approach

Author

Oladipo, Elijah Kolawole, Akinleye, Temitope Michael, Adeyemo, Stephen Feranmi, Akinboade, Modinat Wuraola, Siyanbola, Kehinde Favour, Adetunji, Victoria Ademide, Arowosegbe, Olukayode Abimbola, Olatunji, Victoria Kehinde, Adaramola, Esther Oluwadarasimi, Afolabi, Hezekiah Omotayo, Ajani, Christianah Damilola, Siyanbola, Taiwo Pleasure, Folakanmi, Elizabeth Oluwatoyin, Irewolede, Boluwatife Ayobami, Okesanya, Olalekan John, Ajani, Olumide Faith, Ariyo, Olumuyiwa Elijah, Jimah, Esther Moradeyo, Iwalokun, Bamidele Abiodun, Kolawole, Olatunji Matthew, Oloke, Julius Kola, and Onyeaka, Helen

Published
2024
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7. Euclid. I. Overview of the Euclid mission

Author

Euclid Collaboration, Mellier, Y., Abdurro'uf, Barroso, J. A. Acevedo, Achúcarro, A., Adamek, J., Adam, R., Addison, G. E., Aghanim, N., Aguena, M., Ajani, V., Akrami, Y., Al-Bahlawan, A., Alavi, A., Albuquerque, I. S., Alestas, G., Alguero, G., Allaoui, A., Allen, S. W., Allevato, V., Alonso-Tetilla, A. V., Altieri, B., Alvarez-Candal, A., Alvi, S., Amara, A., Amendola, L., Amiaux, J., Andika, I. T., Andreon, S., Andrews, A., Angora, G., Angulo, R. E., Annibali, F., Anselmi, A., Anselmi, S., Arcari, S., Archidiacono, M., Aricò, G., Arnaud, M., Arnouts, S., Asgari, M., Asorey, J., Atayde, L., Atek, H., Atrio-Barandela, F., Aubert, M., Aubourg, E., Auphan, T., Auricchio, N., Aussel, B., Aussel, H., Avelino, P. P., Avgoustidis, A., Avila, S., Awan, S., Azzollini, R., Baccigalupi, C., Bachelet, E., Bacon, D., Baes, M., Bagley, M. B., Bahr-Kalus, B., Balaguera-Antolinez, A., Balbinot, E., Balcells, M., Baldi, M., Baldry, I., Balestra, A., Ballardini, M., Ballester, O., Balogh, M., Bañados, E., Barbier, R., Bardelli, S., Baron, M., Barreiro, T., Barrena, R., Barriere, J. -C., Barros, B. J., Barthelemy, A., Bartolo, N., Basset, A., Battaglia, P., Battisti, A. J., Baugh, C. M., Baumont, L., Bazzanini, L., Beaulieu, J. -P., Beckmann, V., Belikov, A. N., Bel, J., Bellagamba, F., Bella, M., Bellini, E., Benabed, K., Bender, R., Benevento, G., Bennett, C. L., Benson, K., Bergamini, P., Bermejo-Climent, J. R., Bernardeau, F., Bertacca, D., Berthe, M., Berthier, J., Bethermin, M., Beutler, F., Bevillon, C., Bhargava, S., Bhatawdekar, R., Bianchi, D., Bisigello, L., Biviano, A., Blake, R. P., Blanchard, A., Blazek, J., Blot, L., Bosco, A., Bodendorf, C., Boenke, T., Böhringer, H., Boldrini, P., Bolzonella, M., Bonchi, A., Bonici, M., Bonino, D., Bonino, L., Bonvin, C., Bon, W., Booth, J. T., Borgani, S., Borlaff, A. S., Borsato, E., Bose, B., Botticella, M. T., Boucaud, A., Bouche, F., Boucher, J. S., Boutigny, D., Bouvard, T., Bouwens, R., Bouy, H., Bowler, R. A. A., Bozza, V., Bozzo, E., Branchini, E., Brando, G., Brau-Nogue, S., Brekke, P., Bremer, M. N., Brescia, M., Breton, M. -A., Brinchmann, J., Brinckmann, T., Brockley-Blatt, C., Brodwin, M., Brouard, L., Brown, M. L., Bruton, S., Bucko, J., Buddelmeijer, H., Buenadicha, G., Buitrago, F., Burger, P., Burigana, C., Busillo, V., Busonero, D., Cabanac, R., Cabayol-Garcia, L., Cagliari, M. S., Caillat, A., Caillat, L., Calabrese, M., Calabro, A., Calderone, G., Calura, F., Quevedo, B. Camacho, Camera, S., Campos, L., Canas-Herrera, G., Candini, G. P., Cantiello, M., Capobianco, V., Cappellaro, E., Cappelluti, N., Cappi, A., Caputi, K. I., Cara, C., Carbone, C., Cardone, V. F., Carella, E., Carlberg, R. G., Carle, M., Carminati, L., Caro, F., Carrasco, J. M., Carretero, J., Carrilho, P., Duque, J. Carron, Carry, B., Carvalho, A., Carvalho, C. S., Casas, R., Casas, S., Casenove, P., Casey, C. M., Cassata, P., Castander, F. J., Castelao, D., Castellano, M., Castiblanco, L., Castignani, G., Castro, T., Cavet, C., Cavuoti, S., Chabaud, P. -Y., Chambers, K. C., Charles, Y., Charlot, S., Chartab, N., Chary, R., Chaumeil, F., Cho, H., Chon, G., Ciancetta, E., Ciliegi, P., Cimatti, A., Cimino, M., Cioni, M. -R. L., Claydon, R., Cleland, C., Clément, B., Clements, D. L., Clerc, N., Clesse, S., Codis, S., Cogato, F., Colbert, J., Cole, R. E., Coles, P., Collett, T. E., Collins, R. S., Colodro-Conde, C., Colombo, C., Combes, F., Conforti, V., Congedo, G., Conseil, S., Conselice, C. J., Contarini, S., Contini, T., Conversi, L., Cooray, A. R., Copin, Y., Corasaniti, P. -S., Corcho-Caballero, P., Corcione, L., Cordes, O., Corpace, O., Correnti, M., Costanzi, M., Costille, A., Courbin, F., Mifsud, L. Courcoult, Courtois, H. M., Cousinou, M. -C., Covone, G., Cowell, T., Cragg, C., Cresci, G., Cristiani, S., Crocce, M., Cropper, M., Crouzet, P. E, Csizi, B., Cuby, J. -G., Cucchetti, E., Cucciati, O., Cuillandre, J. -C., Cunha, P. A. C., Cuozzo, V., Daddi, E., D'Addona, M., Dafonte, C., Dagoneau, N., Dalessandro, E., Dalton, G. B., D'Amico, G., Dannerbauer, H., Danto, P., Das, I., Da Silva, A., da Silva, R., Doumerg, W. d'Assignies, Daste, G., Davies, J. E., Davini, S., Dayal, P., de Boer, T., Decarli, R., De Caro, B., Degaudenzi, H., Degni, G., de Jong, J. T. A., de la Bella, L. F., de la Torre, S., Delhaise, F., Delley, D., Delucchi, G., De Lucia, G., Denniston, J., De Paolis, F., De Petris, M., Derosa, A., Desai, S., Desjacques, V., Despali, G., Desprez, G., De Vicente-Albendea, J., Deville, Y., Dias, J. D. F., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Diego, J. M., Di Ferdinando, D., Di Giorgio, A. M., Dimauro, P., Dinis, J., Dolag, K., Dolding, C., Dole, H., Sánchez, H. Domínguez, Doré, O., Dournac, F., Douspis, M., Dreihahn, H., Droge, B., Dryer, B., Dubath, F., Duc, P. -A., Ducret, F., Duffy, C., Dufresne, F., Duncan, C. A. J., Dupac, X., Duret, V., Durrer, R., Durret, F., Dusini, S., Ealet, A., Eggemeier, A., Eisenhardt, P. R. M., Elbaz, D., Elkhashab, M. Y., Ellien, A., Endicott, J., Enia, A., Erben, T., Vigo, J. A. Escartin, Escoffier, S., Sanz, I. Escudero, Essert, J., Ettori, S., Ezziati, M., Fabbian, G., Fabricius, M., Fang, Y., Farina, A., Farina, M., Farinelli, R., Farrens, S., Faustini, F., Feltre, A., Ferguson, A. M. N., Ferrando, P., Ferrari, A. G., Ferré-Mateu, A., Ferreira, P. G., Ferreras, I., Ferrero, I., Ferriol, S., Ferruit, P., Filleul, D., Finelli, F., Finkelstein, S. L., Finoguenov, A., Fiorini, B., Flentge, F., Focardi, P., Fonseca, J., Fontana, A., Fontanot, F., Fornari, F., Fosalba, P., Fossati, M., Fotopoulou, S., Fouchez, D., Fourmanoit, N., Frailis, M., Fraix-Burnet, D., Franceschi, E., Franco, A., Franzetti, P., Freihoefer, J., Frenk, C. . S., Frittoli, G., Frugier, P. -A., Frusciante, N., Fumagalli, A., Fumagalli, M., Fumana, M., Fu, Y., Gabarra, L., Galeotta, S., Galluccio, L., Ganga, K., Gao, H., García-Bellido, J., Garcia, K., Gardner, J. P., Garilli, B., Gaspar-Venancio, L. -M., Gasparetto, T., Gautard, V., Gavazzi, R., Gaztanaga, E., Genolet, L., Santos, R. Genova, Gentile, F., George, K., Gerbino, M., Ghaffari, Z., Giacomini, F., Gianotti, F., Gibb, G. P. S., Gillard, W., Gillis, B., Ginolfi, M., Giocoli, C., Girardi, M., Giri, S. K., Goh, L. W. K., Gómez-Alvarez, P., Gonzalez-Perez, V., Gonzalez, A. H., Gonzalez, E. J., Gonzalez, J. C., Beauchamps, S. Gouyou, Gozaliasl, G., Gracia-Carpio, J., Grandis, S., Granett, B. R., Granvik, M., Grazian, A., Gregorio, A., Grenet, C., Grillo, C., Grupp, F., Gruppioni, C., Gruppuso, A., Guerbuez, C., Guerrini, S., Guidi, M., Guillard, P., Gutierrez, C. M., Guttridge, P., Guzzo, L., Gwyn, S., Haapala, J., Haase, J., Haddow, C. R., Hailey, M., Hall, A., Hall, D., Hamaus, N., Haridasu, B. S., Harnois-Déraps, J., Harper, C., Hartley, W. G., Hasinger, G., Hassani, F., Hatch, N. A., Haugan, S. V. H., Häußler, B., Heavens, A., Heisenberg, L., Helmi, A., Helou, G., Hemmati, S., Henares, K., Herent, O., Hernández-Monteagudo, C., Heuberger, T., Hewett, P. C., Heydenreich, S., Hildebrandt, H., Hirschmann, M., Hjorth, J., Hoar, J., Hoekstra, H., Holland, A. D., Holliman, M. S., Holmes, W., Hook, I., Horeau, B., Hormuth, F., Hornstrup, A., Hosseini, S., Hu, D., Hudelot, P., Hudson, M. J., Huertas-Company, M., Huff, E. M., Hughes, A. C. N., Humphrey, A., Hunt, L. K., Huynh, D. D., Ibata, R., Ichikawa, K., Iglesias-Groth, S., Ilbert, O., Ilić, S., Ingoglia, L., Iodice, E., Israel, H., Israelsson, U. E., Izzo, L., Jablonka, P., Jackson, N., Jacobson, J., Jafariyazani, M., Jahnke, K., Jain, B., Jansen, H., Jarvis, M. J., Jasche, J., Jauzac, M., Jeffrey, N., Jhabvala, M., Jimenez-Teja, Y., Muñoz, A. Jimenez, Joachimi, B., Johansson, P. H., Joudaki, S., Jullo, E., Kajava, J. J. E., Kang, Y., Kannawadi, A., Kansal, V., Karagiannis, D., Kärcher, M., Kashlinsky, A., Kazandjian, M. V., Keck, F., Keihänen, E., Kerins, E., Kermiche, S., Khalil, A., Kiessling, A., Kiiveri, K., Kilbinger, M., Kim, J., King, R., Kirkpatrick, C. C., Kitching, T., Kluge, M., Knabenhans, M., Knapen, J. H., Knebe, A., Kneib, J. -P., Kohley, R., Koopmans, L. V. E., Koskinen, H., Koulouridis, E., Kou, R., Kovács, A., Kovačić, I., Kowalczyk, A., Koyama, K., Kraljic, K., Krause, O., Kruk, S., Kubik, B., Kuchner, U., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lacasa, F., Lacey, C. G., La Franca, F., Lagarde, N., Lahav, O., Laigle, C., La Marca, A., La Marle, O., Lamine, B., Lam, M. C., Lançon, A., Landt, H., Langer, M., Lapi, A., Larcheveque, C., Larsen, S. S., Lattanzi, M., Laudisio, F., Laugier, D., Laureijs, R., Laurent, V., Lavaux, G., Lawrenson, A., Lazanu, A., Lazeyras, T., Boulc'h, Q. Le, Brun, A. M. C. Le, Brun, V. Le, Leclercq, F., Lee, S., Graet, J. Le, Legrand, L., Leirvik, K. N., Jeune, M. Le, Lembo, M., Mignant, D. Le, Lepinzan, M. D., Lepori, F., Reun, A. Le, Leroy, G., Lesci, G. F., Lesgourgues, J., Leuzzi, L., Levi, M. E., Liaudat, T. I., Libet, G., Liebing, P., Ligori, S., Lilje, P. B., Lin, C. -C., Linde, D., Linder, E., Lindholm, V., Linke, L., Li, S. -S., Liu, S. J., Lloro, I., Lobo, F. S. N., Lodieu, N., Lombardi, M., Lombriser, L., Lonare, P., Longo, G., López-Caniego, M., Lopez, X. Lopez, Alvarez, J. Lorenzo, Loureiro, A., Loveday, J., Lusso, E., Macias-Perez, J., Maciaszek, T., Maggio, G., Magliocchetti, M., Magnard, F., Magnier, E. A., Magro, A., Mahler, G., Mainetti, G., Maino, D., Maiorano, E., Malavasi, N., Mamon, G. A., Mancini, C., Mandelbaum, R., Manera, M., Manjón-García, A., Mannucci, F., Mansutti, O., Outeiro, M. Manteiga, Maoli, R., Maraston, C., Marcin, S., Marcos-Arenal, P., Margalef-Bentabol, B., Marggraf, O., Marinucci, D., Marinucci, M., Markovic, K., Marleau, F. R., Marpaud, J., Martignac, J., Martín-Fleitas, J., Martin-Moruno, P., Martin, E. L., Martinelli, M., Martinet, N., Martin, H., Martins, C. J. A. P., Marulli, F., Massari, D., Massey, R., Masters, D. C., Matarrese, S., Matsuoka, Y., Matthew, S., Maughan, B. J., Mauri, N., Maurin, L., Maurogordato, S., McCarthy, K., McConnachie, A. W., McCracken, H. J., McDonald, I., McEwen, J. D., McPartland, C. J. R., Medinaceli, E., Mehta, V., Mei, S., Melchior, M., Melin, J. -B., Ménard, B., Mendes, J., Mendez-Abreu, J., Meneghetti, M., Mercurio, A., Merlin, E., Metcalf, R. B., Meylan, G., Migliaccio, M., Mignoli, M., Miller, L., Miluzio, M., Milvang-Jensen, B., Mimoso, J. P., Miquel, R., Miyatake, H., Mobasher, B., Mohr, J. J., Monaco, P., Monguió, M., Montoro, A., Mora, A., Dizgah, A. Moradinezhad, Moresco, M., Moretti, C., Morgante, G., Morisset, N., Moriya, T. J., Morris, P. W., Mortlock, D. J., Moscardini, L., Mota, D. F., Mottet, S., Moustakas, L. A., Moutard, T., Müller, T., Munari, E., Murphree, G., Murray, C., Murray, N., Musi, P., Nadathur, S., Nagam, B. C., Nagao, T., Naidoo, K., Nakajima, R., Nally, C., Natoli, P., Navarro-Alsina, A., Girones, D. Navarro, Neissner, C., Nersesian, A., Nesseris, S., Nguyen-Kim, H. N., Nicastro, L., Nichol, R. C., Nielbock, M., Niemi, S. -M., Nieto, S., Nilsson, K., Noller, J., Norberg, P., Nouri-Zonoz, A., Ntelis, P., Nucita, A. A., Nugent, P., Nunes, N. J., Nutma, T., Ocampo, I., Odier, J., Oesch, P. A., Oguri, M., Oliveira, D. Magalhaes, Onoue, M., Oosterbroek, T., Oppizzi, F., Ordenovic, C., Osato, K., Pacaud, F., Pace, F., Padilla, C., Paech, K., Pagano, L., Page, M. J., Palazzi, E., Paltani, S., Pamuk, S., Pandolfi, S., Paoletti, D., Paolillo, M., Papaderos, P., Pardede, K., Parimbelli, G., Parmar, A., Partmann, C., Pasian, F., Passalacqua, F., Paterson, K., Patrizii, L., Pattison, C., Paulino-Afonso, A., Paviot, R., Peacock, J. A., Pearce, F. R., Pedersen, K., Peel, A., Peletier, R. F., Ibanez, M. Pellejero, Pello, R., Penny, M. T., Percival, W. J., Perez-Garrido, A., Perotto, L., Pettorino, V., Pezzotta, A., Pezzuto, S., Philippon, A., Pierre, M., Piersanti, O., Pietroni, M., Piga, L., Pilo, L., Pires, S., Pisani, A., Pizzella, A., Pizzuti, L., Plana, C., Polenta, G., Pollack, J. E., Poncet, M., Pöntinen, M., Pool, P., Popa, L. A., Popa, V., Popp, J., Porciani, C., Porth, L., Potter, D., Poulain, M., Pourtsidou, A., Pozzetti, L., Prandoni, I., Pratt, G. W., Prezelus, S., Prieto, E., Pugno, A., Quai, S., Quilley, L., Racca, G. D., Raccanelli, A., Rácz, G., Radinović, S., Radovich, M., Ragagnin, A., Ragnit, U., Raison, F., Ramos-Chernenko, N., Ranc, C., Rasera, Y., Raylet, N., Rebolo, R., Refregier, A., Reimberg, P., Reiprich, T. H., Renk, F., Renzi, A., Retre, J., Revaz, Y., Reylé, C., Reynolds, L., Rhodes, J., Ricci, F., Ricci, M., Riccio, G., Ricken, S. O., Rissanen, S., Risso, I., Rix, H. -W., Robin, A. C., Rocca-Volmerange, B., Rocci, P. -F., Rodenhuis, M., Rodighiero, G., Monroy, M. Rodriguez, Rollins, R. P., Romanello, M., Roman, J., Romelli, E., Romero-Gomez, M., Roncarelli, M., Rosati, P., Rosset, C., Rossetti, E., Roster, W., Rottgering, H. J. A., Rozas-Fernández, A., Ruane, K., Rubino-Martin, J. A., Rudolph, A., Ruppin, F., Rusholme, B., Sacquegna, S., Sáez-Casares, I., Saga, S., Saglia, R., Sahlén, M., Saifollahi, T., Sakr, Z., Salvalaggio, J., Salvaterra, R., Salvati, L., Salvato, M., Salvignol, J. -C., Sánchez, A. G., Sanchez, E., Sanders, D. B., Sapone, D., Saponara, M., Sarpa, E., Sarron, F., Sartori, S., Sartoris, B., Sassolas, B., Sauniere, L., Sauvage, M., Sawicki, M., Scaramella, R., Scarlata, C., Scharré, L., Schaye, J., Schewtschenko, J. A., Schindler, J. -T., Schinnerer, E., Schirmer, M., Schmidt, F., Schmidt, M., Schneider, A., Schneider, M., Schneider, P., Schöneberg, N., Schrabback, T., Schultheis, M., Schulz, S., Schuster, N., Schwartz, J., Sciotti, D., Scodeggio, M., Scognamiglio, D., Scott, D., Scottez, V., Secroun, A., Sefusatti, E., Seidel, G., Seiffert, M., Sellentin, E., Selwood, M., Semboloni, E., Sereno, M., Serjeant, S., Serrano, S., Setnikar, G., Shankar, F., Sharples, R. M., Short, A., Shulevski, A., Shuntov, M., Sias, M., Sikkema, G., Silvestri, A., Simon, P., Sirignano, C., Sirri, G., Skottfelt, J., Slezak, E., Sluse, D., Smith, G. P., Smith, L. C., Smith, R. E., Smit, S. J. A., Soldano, F., Solheim, B. G. B., Sorce, J. G., Sorrenti, F., Soubrie, E., Spinoglio, L., Mancini, A. Spurio, Stadel, J., Stagnaro, L., Stanco, L., Stanford, S. A., Starck, J. -L., Stassi, P., Steinwagner, J., Stern, D., Stone, C., Strada, P., Strafella, F., Stramaccioni, D., Surace, C., Sureau, F., Suyu, S. H., Swindells, I., Szafraniec, M., Szapudi, I., Taamoli, S., Talia, M., Tallada-Crespí, P., Tanidis, K., Tao, C., Tarrío, P., Tavagnacco, D., Taylor, A. N., Taylor, J. E., Taylor, P. L., Teixeira, E. M., Tenti, M., Idiago, P. Teodoro, Teplitz, H. I., Tereno, I., Tessore, N., Testa, V., Testera, G., Tewes, M., Teyssier, R., Theret, N., Thizy, C., Thomas, P. D., Toba, Y., Toft, S., Toledo-Moreo, R., Tolstoy, E., Tommasi, E., Torbaniuk, O., Torradeflot, F., Tortora, C., Tosi, S., Tosti, S., Trifoglio, M., Troja, A., Trombetti, T., Tronconi, A., Tsedrik, M., Tsyganov, A., Tucci, M., Tutusaus, I., Uhlemann, C., Ulivi, L., Urbano, M., Vacher, L., Vaillon, L., Valageas, P., Valdes, I., Valentijn, E. A., Valenziano, L., Valieri, C., Valiviita, J., Broeck, M. Van den, Vassallo, T., Vavrek, R., Vega-Ferrero, J., Venemans, B., Venhola, A., Ventura, S., Kleijn, G. Verdoes, Vergani, D., Verma, A., Vernizzi, F., Veropalumbo, A., Verza, G., Vescovi, C., Vibert, D., Viel, M., Vielzeuf, P., Viglione, C., Viitanen, A., Villaescusa-Navarro, F., Vinciguerra, S., Visticot, F., Voggel, K., von Wietersheim-Kramsta, M., Vriend, W. J., Wachter, S., Walmsley, M., Walth, G., Walton, D. M., Walton, N. A., Wander, M., Wang, L., Wang, Y., Weaver, J. R., Weller, J., Wetzstein, M., Whalen, D. J., Whittam, I. H., Widmer, A., Wiesmann, M., Wilde, J., Williams, O. R., Winther, H. -A., Wittje, A., Wong, J. H. W., Wright, A. H., Yankelevich, V., Yeung, H. W., Yoon, M., Youles, S., Yung, L. Y. A., Zacchei, A., Zalesky, L., Zamorani, G., Vitorelli, A. Zamorano, Marc, M. Zanoni, Zennaro, M., Zerbi, F. M., Zinchenko, I. A., Zoubian, J., Zucca, E., and Zumalacarregui, M.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'

Published
2024

8. Dark Energy Survey Year 3 results: simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps II. Cosmological results

Author

Gatti, M., Campailla, G., Jeffrey, N., Whiteway, L., Porredon, A., Prat, J., Williamson, J., Raveri, M., Jain, B., Ajani, V., Giannini, G., Yamamoto, M., Zhou, C., Blazek, J., Anbajagane, D., Samuroff, S., Kacprzak, T., Alarcon, A., Amon, A., Bechtol, K., Becker, M., Bernstein, G., Campos, A., Chang, C., Chen, R., Choi, A., Davis, C., Derose, J., Diehl, H. T., Dodelson, S., Doux, C., Eckert, K., Elvin-Poole, J., Everett, S., Ferte, A., Gruen, D., Gruendl, R., Harrison, I., Hartley, W. G., Herner, K., Huff, E. M., Jarvis, M., Kuropatkin, N., Leget, P. F., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Pandey, S., Rollins, R. P., Roodman, A., Sanchez, C., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M., Tutusaus, I., Varga, T. N., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Abbott, T. M. C., Aguena, M., Allam, S. S., Alves, O., Andrade-Oliveira, F., Bacon, D., Bocquet, S., Brooks, D., Rosell, A. Carnero, Carretero, J., da Costa, L. N., Pereira, M. E. S., De Vicente, J., Ferrero, I., Frieman, J., García-Bellido, J., Gaztanaga, E., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., Lee, S., Marshall, J. L., Mena-Fernández, J., Miquel, R., Pieres, A., Malagón, A. A. Plazas, Sanchez, E., Cid, D. Sanchez, Schubnell, M., Smith, M., Suchyta, E., Tarle, G., Weaverdyck, N., Weller, J., and Wiseman, P.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years (Y3) of the Dark Energy Survey (DES). We implement: 1) second and third moments; 2) wavelet phase harmonics; 3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven $\nu w$CDM cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the Figure of Merit $\textrm{FoM}(S_8, \Omega_{\textrm{m}})$ is improved by 70 percent ($\Lambda$CDM) and 90 percent ($w$CDM). When all the summary statistics are combined, we achieve a 2 percent constraint on the amplitude of fluctuations parameter $S_8 \equiv \sigma_8 (\Omega_{\textrm{m}}/0.3)^{0.5}$, obtaining $S_8 = 0.794 \pm 0.017$ ($\Lambda$CDM) and $S_8 = 0.817 \pm 0.021$ ($w$CDM). The constraints from different statistics are shown to be internally consistent (with a $p$-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the DES Y3 data, finding good consistency; we also compare with results from external datasets, such as \planck{} constraints from the Cosmic Microwave Background, finding statistical agreement, with discrepancies no greater than $<2.2\sigma$., Comment: 24 pages, 13 figures, to be submitted to PRD. Comments welcome!

Published
2024

16. An optimized strategy triggered at the 2nd immunization visit to prevent HIV acquisition by breastfeeding: a phase 2 trial in Burkina Faso (PREVENIR-PEV)

Author

Mennecier, Anaïs, Sakana, Béninwendé Leticia Delphine, D’Ottavi, Morgana, Tassembedo, Souleymane, Moles, Jean-Pierre, Kania, Dramane, Taofiki, Ajani Ousmane, Kadeba, Franck Edgar, Diallo, Ibrahima, Eymard-Duvernay, Sabrina, Meda, Nicolas, Mosqueira, Beatriz, Fao, Paulin, Nagot, Nicolas, and Vande Perre, Philippe

Published
2024
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19. METI: deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics

Author

Jiang, Jiahui, Liu, Yunhe, Qin, Jiangjiang, Chen, Jianfeng, Wu, Jingjing, Pizzi, Melissa P., Lazcano, Rossana, Yamashita, Kohei, Xu, Zhiyuan, Pei, Guangsheng, Cho, Kyung Serk, Chu, Yanshuo, Sinjab, Ansam, Peng, Fuduan, Yan, Xinmiao, Han, Guangchun, Wang, Ruiping, Dai, Enyu, Dai, Yibo, Czerniak, Bogdan A., Futreal, Andrew, Maitra, Anirban, Lazar, Alexander, Kadara, Humam, Jazaeri, Amir A., Cheng, Xiangdong, Ajani, Jaffer, Gao, Jianjun, Hu, Jian, and Wang, Linghua

Published
2024
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26. Evaluating Active Lecture and Traditional Lecture in Higher Education

Author

Kathleen Klein, Jennifer Calabrese, Adam Aguiar, Sunny Mathew, Kimoni Ajani, Rania Almajid, and Jennifer Aarons

Abstract

The purpose of this study was to evaluate the effectiveness of traditional and active lecture methods in higher-education courses. A multiple group convergent parallel mixed method design was used, with measurement of learning, attention, and student preference for active or traditional lecture methods. Six faculty at a public university in the northeast region of the United States engaged 178 undergraduate and graduate students in a traditional lecture session and an active lecture session during the Spring 2022 semester. Results indicated effectiveness of active and traditional lecture approaches (p < 0.05). Analysis of qualitative and quantitative data in the study provides additional information regarding student preference for active lecture based on perceptions of increased learning benefits, interaction/engagement, attention, activities, discussion, and the use of multimedia. In implementing both traditional and active lecture sessions this study employed pre-lecture and post-lecture quizzes that students found to be very beneficial to learning.

Published
2023

27. Dark Energy Survey Year 3 results: simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps I: validation on simulations

Author

Gatti, M., Jeffrey, N., Whiteway, L., Williamson, J., Jain, B., Ajani, V., Anbajagane, D., Giannini, G., Zhou, C., Porredon, A., Prat, J., Yamamoto, M., Blazek, J., Kacprzak, T., Samuroff, S., Alarcon, A., Amon, A., Bechtol, K., Becker, M., Bernstein, G., Campos, A., Chang, C., Chen, R., Choi, A., Davis, C., Derose, J., Diehl, H. T., Dodelson, S., Doux, C., Eckert, K., Elvin-Poole, J., Everett, S., Ferte, A., Gruen, D., Gruendl, R., Harrison, I., Hartley, W. G., Herner, K., Huff, E. M., Jarvis, M., Kuropatkin, N., Leget, P. F., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Pandey, S., Raveri, M., Rollins, R. P., Roodman, A., Sanchez, C., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M., Tutusaus, I., Varga, T. N., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Aguena, M., Alves, O., Annis, J., Brooks, D., Carretero, J., Castander, F. J., Cawthon, R., da Costa, L. N., De Vicente, J., Desai, S., Ferrero, I., Flaugher, B., Friedel, D., Frieman, J., García-Bellido, J., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., Lee, S., Marshall, J. L., Mena-Fernández, J., Menanteau, F., Miquel, R., Ogando, R. L. C., Pereira, M. E. S., Pieres, A., Malagón, A. A. Plazas, Sanchez, E., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Weaverdyck, N., Weller, J., and Wiseman, P.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Beyond-two-point statistics contain additional information on cosmological as well as astrophysical and observational (systematics) parameters. In this methodology paper we provide an end-to-end simulation-based analysis of a set of Gaussian and non-Gaussian weak lensing statistics using detailed mock catalogues of the Dark Energy Survey. We implement: 1) second and third moments; 2) wavelet phase harmonics (WPH); 3) the scattering transform (ST). Our analysis is fully based on simulations, it spans a space of seven $\nu w$CDM cosmological parameters, and it forward models the most relevant sources of systematics of the data (masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration). We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a likelihood-free-inference approach. We validate the pipeline extensively, and we find that WPH exhibits the strongest performance when combined with second moments, followed by ST. and then by third moments. The combination of all the different statistics further enhances constraints with respect to second moments, up to 25 per cent, 15 per cent, and 90 per cent for $S_8$, $\Omega_{\rm m}$, and the Figure-Of-Merit ${\rm FoM_{S_8,\Omega_{\rm m}}}$, respectively. We further find that non-Gaussian statistics improve constraints on $w$ and on the amplitude of intrinsic alignment with respect to second moments constraints. The methodological advances presented here are suitable for application to Stage IV surveys from Euclid, Rubin-LSST, and Roman with additional validation on mock catalogues for each survey. In a companion paper we present an application to DES Year 3 data., Comment: 25 pages, 18 figures. Comments welcome!

Published
2023

30. SMYD5 methylation of rpL40 links ribosomal output to gastric cancer

Author

Park, Juhyung, Wu, Jibo, Szkop, Krzysztof J., Jeong, Jinho, Jovanovic, Predrag, Husmann, Dylan, Flores, Natasha M., Francis, Joel W., Chen, Ying-Jiun C., Benitez, Ana Morales, Zahn, Emily, Song, Shumei, Ajani, Jaffer A., Wang, Linghua, Singh, Kamini, Larsson, Ola, Garcia, Benjamin A., Topisirovic, Ivan, Gozani, Or, and Mazur, Pawel K.

Published
2024
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32. Reinforcement Learning-assisted Evolutionary Algorithm: A Survey and Research Opportunities

Author

Song, Yanjie, Wu, Yutong, Guo, Yangyang, Yan, Ran, Suganthan, P. N., Zhang, Yue, Pedrycz, Witold, Das, Swagatam, Mallipeddi, Rammohan, and Feng, Oladayo Solomon Ajani. Qiang

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Evolutionary algorithms (EA), a class of stochastic search methods based on the principles of natural evolution, have received widespread acclaim for their exceptional performance in various real-world optimization problems. While researchers worldwide have proposed a wide variety of EAs, certain limitations remain, such as slow convergence speed and poor generalization capabilities. Consequently, numerous scholars actively explore improvements to algorithmic structures, operators, search patterns, etc., to enhance their optimization performance. Reinforcement learning (RL) integrated as a component in the EA framework has demonstrated superior performance in recent years. This paper presents a comprehensive survey on integrating reinforcement learning into the evolutionary algorithm, referred to as reinforcement learning-assisted evolutionary algorithm (RL-EA). We begin with the conceptual outlines of reinforcement learning and the evolutionary algorithm. We then provide a taxonomy of RL-EA. Subsequently, we discuss the RL-EA integration method, the RL-assisted strategy adopted by RL-EA, and its applications according to the existing literature. The RL-assisted procedure is divided according to the implemented functions including solution generation, learnable objective function, algorithm/operator/sub-population selection, parameter adaptation, and other strategies. Additionally, different attribute settings of RL in RL-EA are discussed. In the applications of RL-EA section, we also demonstrate the excellent performance of RL-EA on several benchmarks and a range of public datasets to facilitate a quick comparative study. Finally, we analyze potential directions for future research., Comment: 28 pages, 16 figures

Published
2023

33. Transitive path decompositions of Cartesian products of complete graphs

Author

Gunasekara, Ajani De Vas and Devillers, Alice

Subjects
Mathematics - Combinatorics, Mathematics - Group Theory, 05C38, 05E20, 05C25
Abstract

An $H$-decomposition of a graph $\Gamma$ is a partition of its edge set into subgraphs isomorphic to $H$. A transitive decomposition is a special kind of $H$-decomposition that is highly symmetrical in the sense that the subgraphs (copies of $H$) are preserved and transitively permuted by a group of automorphisms of $\Gamma$. This paper concerns transitive $H$-decompositions of the graph $K_n \Box K_n$ where $H$ is a path. When $n$ is an odd prime, we present a construction for a transitive path decomposition where the paths in the decomposition are considerably large compared to the number of vertices. Our main result supports well-known Gallai's conjecture and an extended version of Ringel's conjecture., Comment: 15 pages, 4 figures

Published
2023

34. Beyond the 3rd moment: A practical study of using lensing convergence CDFs for cosmology with DES Y3

Author

Anbajagane, D., Chang, C., Banerjee, A., Abel, T., Gatti, M., Ajani, V., Alarcon, A., Amon, A., Baxter, E. J., Bechtol, K., Becker, M. R., Bernstein, G. M., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Chen, R., Choi, A., Davis, C., DeRose, J., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Elvin-Poole, J., Everett, S., Fert'e, A., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Huff, E. M., Jain, B., Jarvis, M., Jeffrey, N., Kacprzak, T., Kokron, N., Kuropatkin, N., Leget, P. -F., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Pandey, S., Prat, J., Raveri, M., Rollins, R. P., Roodman, A., Rykoff, E. S., Sanchez, C., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Whiteway, L., Yanny, B., Yin, B., Zhang, Y., Abbott, T. M. C., Allam, S., Aguena, M., Alves, O., Andrade-Oliveira, F., Annis, J., Bacon, D., Blazek, J., Brooks, D., Cawthon, R., da Costa, L. N., Pereira, M. E. S., Davis, T. M., Desai, S., Doel, P., Ferrero, I., Frieman, J., Giannini, G., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., Marshall, J. L., Mena-Fernandez, J., Menanteau, F., Miquel, R., Palmese, A., Pieres, A., Malag'on, A. A. Plazas, Reil, K., Sanchez, E., Smith, M., Swanson, M. E. C., Tarle, G., and Wiseman, P.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Widefield surveys of the sky probe many clustered scalar fields -- such as galaxy counts, lensing potential, gas pressure, etc. -- that are sensitive to different cosmological and astrophysical processes. Our ability to constrain such processes from these fields depends crucially on the statistics chosen to summarize the field. In this work, we explore the cumulative distribution function (CDF) at multiple scales as a summary of the galaxy lensing convergence field. Using a suite of N-body lightcone simulations, we show the CDFs' constraining power is modestly better than that of the 2nd and 3rd moments of the field, as they approximately capture the information from all moments of the field in a concise data vector. We then study the practical aspects of applying the CDFs to observational data, using the first three years of the Dark Energy Survey (DES Y3) data as an example, and compute the impact of different systematics on the CDFs. The contributions from the point spread function are 2-3 orders of magnitude below the cosmological signal, while those from reduced shear approximation contribute $\lesssim 1\%$ to the signal. Source clustering effects and baryon imprints contribute $1-10\%$. Enforcing scale cuts to limit systematics-driven biases in parameter constraints degrades these constraints a noticeable amount, and this degradation is similar for the CDFs and the moments. We also detect correlations between the observed convergence field and the shape noise field at $13\sigma$. We find that the non-Gaussian correlations in the noise field must be modeled accurately to use the CDFs, or other statistics sensitive to all moments, as a rigorous cosmology tool., Comment: 21 pages, 12 figures

Published
2023

35. Detection of the significant impact of source clustering on higher-order statistics with DES Year 3 weak gravitational lensing data

Author

Gatti, M., Jeffrey, N., Whiteway, L., Ajani, V., Kacprzak, T., Zürcher, D., Chang, C., Jain, B., Blazek, J., Krause, E., Alarcon, A., Amon, A., Bechtol, K., Becker, M., Bernstein, G., Campos, A., Chen, R., Choi, A., Davis, C., Derose, J., Diehl, H. T., Dodelson, S., Doux, C., Eckert, K., Elvin-Poole, J., Everett, S., Ferte, A., Gruen, D., Gruendl, R., Harrison, I., Hartley, W. G., Herner, K., Huff, E. M., Jarvis, M., Kuropatkin, N., Leget, P. F., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Pandey, S., Prat, J., Raveri, M., Rollins, R. P., Roodman, A., Sanchez, C., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M., Tutusaus, I., Varga, T. N., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Allam, S. S., Alves, O., Aguena, M., Bacon, D., Bertin, E., Brooks, D., Burke, D. L., Rosell, A. Carnero, Carretero, J., Cawthon, R., da Costa, L. N., Davis, T. M., De Vicente, J., Desai, S., Doel, P., García-Bellido, J., Giannini, G., Gutierrez, G., Ferrero, I., Frieman, J., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., Marshall, J. L., Mena-Fernández, J., Miquel, R., Ogando, R. L. C., Palmese, A., Pereira, M. E. S., Malagón, A. A. Plazas, Rodriguez-Monroy, M., Samuroff, S., Sanchez, E., Schubnell, M., Smith, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Weaverdyck, N., and Wiseman, P.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We demonstrate and measure the impact of source galaxy clustering on higher-order summary statistics of weak gravitational lensing data. By comparing simulated data with galaxies that either trace or do not trace the underlying density field, we show this effect can exceed measurement uncertainties for common higher-order statistics for certain analysis choices. Source clustering effects are larger at small scales and for statistics applied to combinations of low and high redshift samples, and diminish at high redshift. We evaluate the impact on different weak lensing observables, finding that third moments and wavelet phase harmonics are more affected than peak count statistics. Using Dark Energy Survey Year 3 data we construct null tests for the source-clustering-free case, finding a $p$-value of $p=4\times10^{-3}$ (2.6 $\sigma$) using third-order map moments and $p=3\times10^{-11}$ (6.5 $\sigma$) using wavelet phase harmonics. The impact of source clustering on cosmological inference can be either be included in the model or minimized through \textit{ad-hoc} procedures (e.g. scale cuts). We verify that the procedures adopted in existing DES Y3 cosmological analyses (using map moments and peaks) were sufficient to render this effect negligible. Failing to account for source clustering can significantly impact cosmological inference from higher-order gravitational lensing statistics, e.g. higher-order N-point functions, wavelet-moment observables (including phase harmonics and scattering transforms), and deep learning or field level summary statistics of weak lensing maps. We provide recipes both to minimise the impact of source clustering and to incorporate source clustering effects into forward-modelled mock data., Comment: 5 pages, 2 figures, submitted to MNRAS Letters

Published
2023

39. A Fitness-assignment Method for Evolutionary Constrained Multi-objective Optimization

Author

Ajani, Oladayo S., M, Sri Srinivasa Raju, Paul, Anand, and Mallipeddi, Rammohan

Subjects
Computer Science - Neural and Evolutionary Computing
Abstract

The effectiveness of Constrained Multi-Objective Evolutionary Algorithms (CMOEAs) depends on their ability to reach the different feasible regions during evolution, by exploiting the information present in infeasible solutions, in addition to optimizing the several conflicting objectives. Over the years, researchers have proposed several CMOEAs to handle Constrained Multi-objective Optimization Problems (CMOPs). However, most of the proposed CMOEAs with scalable performance are too complex because they are either multi-staged or multi-population-based algorithms. Consequently, to ensure the simplicity of CMOEAs, researchers have proposed different fitness-assignment-based CMOEAs by combining different fitness-assignment-based methods used to solve unconstrained multi-objective problems with information regarding the feasibility of each solution. The main performance drawback of such methods is that it is difficult to design a fitness assignment method that can account for constraint violation in addition to convergence and diversity. Hence in this paper, we propose an effective single-population fitness assignment-based CMOEA referred to as IcSDE+ that can explore different feasible regions in the search space. IcSDE+ is a fitness assignment-based algorithm, that is an efficient fusion of constraint violation (c), Shift-based Density Estimation (SDE), and sum of objectives (+). The performance of IcSDE+ is favorably compared against 9 state-of-the-art CMOEAs on 6 different benchmark suites with diverse characteristics., Comment: 20 pages, 5 main figues

Published
2023

40. Exploring Teachers' Lived Experiences on the Integration of Values Education in South African High Schools

Author

Khathi, Joseph Lamlani, Ajani, Oluwatoyin Ayodele, and Govender, Samantha

Abstract

Values education has become a necessary tool in response to the rise in moral deterioration in an average South African society today. The school is viewed as one of the key players in nurturing children into adulthood. The teaching of values that can give the growing generation, necessary moral development is one of the responsibilities of the schools. Hence, this study aims at exploring teachers' experiences on how they integrate values education into South African learners in various high schools. This qualitative study engaged five schools in its case study, where five teachers from each of the schools were purposively selected for semi-structured focus group interviews, to share their experiences on the integration of moral values in schools. Moral development theory was used to underpin the study. Findings from the inductive thematic analysis from the participants from both rural and urban schools indicated a misunderstanding of the concept of values education by some teachers, which affects its effective integration. The study established that role modelling of learners by teachers and parents are inevitable to save the society from moral decadence, while some participants indicted overpopulation, single parenthood, social media as some of the challenges to the integration of value education in schools. The study, therefore, recommends capacitation of teachers through various professional development programmes, to integrate values education and adequate parental support as some of the strategies to promote effective integration of values education in schools.

Published
2022

41. A Predicting Analysis of Academic Staff's Motivation to Teach Online in a Nigerian University

Author

Itasanmi, Sunday A., Ekpenyong, Violet O., Akintolu, Morakinyo, and Ajani, Oluwatoyin A.

Abstract

This study examined the predictors of academic staff motivation for online teaching in a Nigerian University. Theory of Planned Behaviour served as the conceptual foundation for the study. A survey design was adopted and a total of one hundred and nine-five (195) academic staff participated in the study from a university that was purposefully chosen for the study. A questionnaire tagged 'Academic Staff's Motivation for Online Teaching Survey (SMOTS)' adapted from Chi (2015) was used for data collection. The questionnaire consisted of six domains - demographics, online teaching consideration, perception of online teaching, motivation for online teaching concerning resources, motivation for online teaching with respect to external factors and general motivation to teach online. Data were analyzed using percentages and frequency distribution, mean, standard deviation, multiple regression analysis, Pearson Correlation, T-test, One-Way Analysis of Variance (ANOVA) and Multivariate Analysis of Variance (MANOVA). Results of the study revealed that the perception of online teaching and academic staff's motivation for online teaching regarding external factors had a positive significant contribution to the general motivation of academic staff to teach online. Also, age was found to have a significant influence on academic staff's motivation to teach online indicators (perception of teaching online, motivation to teach online regarding resources, and motivation to teach online regarding external factors). Hence, it was concluded that adequate consideration must be given to these identified contributing factors to motivation for online teaching among academic staff by those who design and implement online teaching initiatives in the university to sustain academic staff's interest in online teaching over time. Equally, policy decisions on online teaching in the university should be based on clear objectives for the generality of the academic staff irrespective of age, gender, marital status, and faculty rank.

Published
2022

42. The Use of Modal Auxiliary Verbs among Selected Pre-Service Students at a South African Rural University

Author

Luvuno, Monica Dudu and Ajani, Oluwatoyin Ayodele

Abstract

This study was conducted at a university based in KwaZulu-Natal, South Africa. The purpose of the study was to determine if the explicit instruction of selected grammar aspect, modal auxiliary verbs, improved students' ability to write English. The study was qualitative in nature and a case study design was adopted. The focus was in relation to a sample of 80 student teachers who were randomly selected in 2016 in the Faculty of Education. 40 participants were randomly assigned into experimental and control groups. For the experimental group, training lasted six weeks. Both groups were made to write similar essays and those essays were marked focusing on the students' ability to use modal auxiliary verbs. The study's findings revealed that the experimental group performed better than those in the control group in the use of modal auxiliary verbs. Based on the findings, the study recommended explicit grammar instruction in all the students' level of study in order to overcome the challenges they have in writing English. Thus, time should be created to ascertain that adequate explicit grammar lessons are offered to all pre-service teachers at the university.

Published
2022

43. Evaluating the Promotion Requirements for the Appointment of Office-Based Educators in the Department of Basic Education in South Africa

Author

Mbokazi, Msawenkosi Sandile, Mkhasibe, Rachel Gugu, and Ajani, Oluwatoyin Ayodele

Abstract

Various promotion requirements are adopted in the appointment of classroom or subject educators as office-based educators or subject advisors (education specialists) in the Department of Basic Education. This qualitative adopted interpretive paradigm study sought to explore educators' lived experiences on the promotion requirements espoused by the Department for the appointment of qualified educators as office-based educators. Ten educator-participants were purposively selected for a semi-structured, face-to-face interview to collect in-depth data for the study. Collected data were thematically analysed to generate themes for the presentation and discussion of findings. The promotion requirements for office-based educators are inadequately utilised in the selection of suitable candidates for the posts. The study established an unfair promotion process in the appointment of office-based educators, and thus, many qualified educators are disadvantaged. The study recommends that promotion requirements should be adhered to in the selection process, to ensure fairness and social justice for all qualified candidates.

Published
2022

44. Exploring the Adoption and Usage of Learning Management System as Alternative for Curriculum Delivery in South African Higher Education Institutions during COVID-19 Lockdown

Author

Gamede, Bongani T., Ajani, Oluwatoyin Ayodele, and Afolabi, Olufemi Sunday

Abstract

This study adopted a discursive approach to review the use of the Learning Management System (LMS) popularly known as "Moodle" in most South African universities. Moodle as fondly called is one of the online tools that can be effectively used to deliver learning activities as well as online learning assessments to implement curriculum delivery without borders or disruptions during the COVID-19 lockdown across the globe. The author highlights various extant studies on the usage and adoption of LMS into teaching and learning for effective implementation in higher institutions of learning. LMS is a global online tool that has been in use for decades in various higher institutions of learning across the developed countries. It has proved to be an efficient learning platform that has impacted significantly the education sector in these developed countries, as learning experiences are provided to diverse students at their comfort zones. With the break of the COVID-19 pandemic that affects the global world, teaching and learning in most parts of the developed countries continue to be facilitated through various online approaches that include LMS in the developed countries. Unfortunately, the pandemic lockdown in many developing countries like South Africa grossly impacted the delivery of curriculum and educational activities in various learning institutions for several months. The continuous presence of COVID-19 led the South African Department of Higher Education and Training to review approaches to curriculum delivery to salvage academic activities. Thus, declared online learning as an alternative to face-to-face curriculum delivery in higher institutions. The adoption of LMS results as the best approach to engage students in full teaching and learning activities.

Published
2022

45. Euclid Preparation. XXVIII. Forecasts for ten different higher-order weak lensing statistics

Author

Euclid Collaboration, Ajani, V., Baldi, M., Barthelemy, A., Boyle, A., Burger, P., Cardone, V. F., Cheng, S., Codis, S., Giocoli, C., Harnois-Déraps, J., Heydenreich, S., Kansal, V., Kilbinger, M., Linke, L., Llinares, C., Martinet, N., Parroni, C., Peel, A., Pires, S., Porth, L., Tereno, I., Uhlemann, C., Vicinanza, M., Vinciguerra, S., Aghanim, N., Auricchio, N., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Dupac, X., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., Gillis, B., Grazian, A., Grupp, F., Hoekstra, H., Holmes, W., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Kümmel, M., Kitching, T., Kunz, M., Kurki-Suonio, H., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Mei, S., Mellier, Y., Meneghetti, M., Moresco, M., Moscardini, L., Niemi, S. -M., Nightingale, J., Nutma, T., Padilla, C., Paltani, S., Pedersen, K., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Boucaud, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Fabbian, G., Farina, M., Graciá-Carpio, J., Keihänen, E., Lindholm, V., Maino, D., Mauri, N., Neissner, C., Schirmer, M., Scottez, V., Zucca, E., Akrami, Y., Baccigalupi, C., Balaguera-Antolínez, A., Ballardini, M., Bernardeau, F., Biviano, A., Blanchard, A., Borgani, S., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Castro, T., Chambers, K. C., Cooray, A. R., Coupon, J., Courtois, H. M., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Dole, H., Escartin, J. A., Escoffier, S., Ferrero, I., Finelli, F., Ganga, K., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Muñoz, A. Jimenez, Joachimi, B., Kajava, J. J. E., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Magliocchetti, M., Maoli, R., Marcin, S., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Popa, V., Potter, D., Pourtsidou, A., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Schneider, A., Sefusatti, E., Sereno, M., Shulevski, A., Mancini, A. Spurio, Steinwagner, J., Teyssier, R., Valiviita, J., Veropalumbo, A., Viel, M., and Zinchenko, I. A.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare, and combine the constraining power of ten different HOS on a common set of $Euclid$-like mocks, derived from N-body simulations. In this first paper of the HOWLS series, we computed the nontomographic ($\Omega_{\rm m}$, $\sigma_8$) Fisher information for the one-point probability distribution function, peak counts, Minkowski functionals, Betti numbers, persistent homology Betti numbers and heatmap, and scattering transform coefficients, and we compare them to the shear and convergence two-point correlation functions in the absence of any systematic bias. We also include forecasts for three implementations of higher-order moments, but these cannot be robustly interpreted as the Gaussian likelihood assumption breaks down for these statistics. Taken individually, we find that each HOS outperforms the two-point statistics by a factor of around two in the precision of the forecasts with some variations across statistics and cosmological parameters. When combining all the HOS, this increases to a $4.5$ times improvement, highlighting the immense potential of HOS for cosmic shear cosmological analyses with $Euclid$. The data used in this analysis are publicly released with the paper., Comment: 33 pages, 24 figures, main results in Fig. 19 & Table 5, version published in A&A

Published
2023
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46. Trastuzumab deruxtecan in patients in the USA and Europe with HER2-positive advanced gastric or gastroesophageal junction cancer with disease progression on or after a trastuzumab-containing regimen (DESTINY-Gastric02): primary and updated analyses from a single-arm, phase 2 study.

Author

Van Cutsem, Eric, di Bartolomeo, Maria, Smyth, Elizabeth, Chau, Ian, Park, Haeseong, Siena, Salvatore, Lonardi, Sara, Wainberg, Zev, Ajani, Jaffer, Chao, Joseph, Janjigian, Yelena, Qin, Amy, Singh, Jasmeet, Barlaskar, Ferdous, Kawaguchi, Yoshinori, and Ku, Geoffrey

Subjects
Female, Humans, Male, Middle Aged, Antibodies, Monoclonal, Humanized, Antineoplastic Combined Chemotherapy Protocols, Disease Progression, Esophageal Neoplasms, Esophagogastric Junction, Immunoconjugates, Receptor, ErbB-2, Stomach Neoplasms, Trastuzumab, Aged
Abstract

BACKGROUND: Approximately 15-20% of advanced gastric and gastro-oesophageal junction cancers overexpress HER2. In DESTINY-Gastric01, the HER2-targeted antibody-drug conjugate trastuzumab deruxtecan improved response and overall survival versus chemotherapy in patients from Japan and South Korea with locally advanced or metastatic HER2-positive gastric or gastro-oesophageal junction cancer whose disease progressed after two lines of previous therapy including trastuzumab. Here, we report primary and updated analyses of the single-arm, phase 2 DESTINY-Gastric02 trial, which aimed to examine trastuzumab deruxtecan in patients living in the USA and Europe. METHODS: DESTINY-Gastric02 is a single-arm, phase 2 study in adult patients from 24 study sites in the USA and Europe (Belgium, Spain, Italy, and the UK). Eligible patients were aged at least 18 years and had an Eastern Cooperative Oncology Group performance status of 0 or 1, pathologically documented unresectable or metastatic gastric or gastro-oesophageal junction cancer, progressive disease on or after first-line therapy with a trastuzumab-containing regimen, with at least one measurable lesion per Response Evaluation Criteria in Solid Tumours (version 1.1), and centrally confirmed HER2-positive disease on a postprogression biopsy. Patients were given 6·4 mg/kg of trastuzumab deruxtecan intravenously every 3 weeks until disease progression, withdrawal by patient, physician decision, or death. The primary endpoint was confirmed objective response rate by independent central review. The primary endpoint and safety were assessed in the full analysis set (ie, participants who received at least one dose of study drug). Here, we report the primary analysis of this study, with a data cutoff of April 9, 2021, and an updated analysis, with a data cutoff of Nov 8, 2021. This trial is registered with ClinicalTrials.gov, NCT04014075, and is ongoing. FINDINGS: Between Nov 26, 2019, and Dec 2, 2020, 89 patients were screened and 79 were enrolled and subsequently treated with trastuzumab deruxtecan (median age 60·7 years [IQR 52·0-68·3], 57 [72%] of 79 were male, 22 [28%] were female, 69 [87%] were White, four [5%] were Asian, one [1%] was Black or African American, one [1%] was Native Hawaiian or Pacific Islander, one had missing race, and three [4%] were other races). At the primary analysis (median follow-up 5·9 months [IQR 4·6-8·6 months]), confirmed objective response was reported in 30 (38% [95% CI 27·3-49·6]) of 79 patients, including three (4%) complete responses and 27 (34%) partial responses, as assessed by independent central review. As of data cutoff for the updated analysis (median follow-up 10·2 months [IQR 5·6-12·9]), a confirmed objective response was reported in 33 (42% [95% CI 30·8-53·4]) of 79 patients, including four (5%) complete responses and 29 (37%) partial responses, as assessed by independent central review. The most common grade 3 or worse treatment-emergent adverse events were anaemia (11 [14%]), nausea (six [8%]), decreased neutrophil count (six [8%]), and decreased white blood cell count (five [6%]). Drug-related serious treatment-emergent adverse events occurred in ten patients (13%). Deaths determined to be associated with study treatment occurred in two patients (3%) and were due to interstitial lung disease or pneumonitis. INTERPRETATION: These clinically meaningful results support the use of trastuzumab deruxtecan as second-line therapy in patients with HER2-positive advanced gastric or gastro-oesophageal junction cancer. FUNDING: Daiichi Sankyo and AstraZeneca.

Published
2023

47. National multicentered retrospective review of clinical and intraoperative factors associated with the development of cerebellar mutism after pediatric posterior fossa tumor resection

Author

Kameda-Smith, Michelle M., Ragulojan, Malavan, Elliott, Cameron, Bliss, Lori, Moore, Hanna, Sader, Nicholas, Alsuwaihel, Mosaab, Tso, Michael K., Dakson, Ayoub, Ajani, Olufemi, Yarascavitch, Blake, Fleming, Adam, Mehta, Vivek, Aminnejad, Minoo, Farrokhyar, Forough, and Singh, Sheila K.

Published
2024
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49. Starlet higher order statistics for galaxy clustering and weak lensing

Author

Ajani, Virginia, Harnois-Déraps, Joachim, Pettorino, Valeria, and Starck, Jean-Luc

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We present a first application to photometric galaxy clustering and weak lensing of wavelet based multi-scale higher order summary statistics: starlet peak counts and starlet $\ell_1$-norm. Peak counts are the local maxima in the map and the $\ell_1$-norm is computed via the sum of the absolute values of the starlet (wavelet) decomposition coefficients of a map, providing a fast multi-scale calculation of the pixel distribution, encoding the information of all pixels in the map. We employ the cosmo-SLICS simulations sources and lenses catalogues and we compute wavelet based higher order statistics in the context of combined probes and their potential when applied to the weak lensing convergence maps and galaxy maps. We get forecasts on the matter density parameter $\Omega_{\rm m}$, the reduced Hubble constant $h$, the matter fluctuation amplitude $\sigma_8$, and the dark energy equation of state parameter $w_0$. We find that, in our setting for this first application, considering the two probes as independent, starlet peaks and the $\ell_1$-norm represent interesting summary statistics that can improve the constraints with respect to the power spectrum also in the case of photometric galaxy clustering and when the two probes are combined., Comment: A&A Letters to the Editor, Forthcoming article, accepted

Published
2022
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50. GridShift: A Faster Mode-seeking Algorithm for Image Segmentation and Object Tracking

Author

Kumar, Abhishek, Ajani, Oladayo S., Das, Swagatam, and Mallipeddi, Rammohan

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

In machine learning and computer vision, mean shift (MS) qualifies as one of the most popular mode-seeking algorithms used for clustering and image segmentation. It iteratively moves each data point to the weighted mean of its neighborhood data points. The computational cost required to find the neighbors of each data point is quadratic to the number of data points. Consequently, the vanilla MS appears to be very slow for large-scale datasets. To address this issue, we propose a mode-seeking algorithm called GridShift, with significant speedup and principally based on MS. To accelerate, GridShift employs a grid-based approach for neighbor search, which is linear in the number of data points. In addition, GridShift moves the active grid cells (grid cells associated with at least one data point) in place of data points towards the higher density, a step that provides more speedup. The runtime of GridShift is linear in the number of active grid cells and exponential in the number of features. Therefore, it is ideal for large-scale low-dimensional applications such as object tracking and image segmentation. Through extensive experiments, we showcase the superior performance of GridShift compared to other MS-based as well as state-of-the-art algorithms in terms of accuracy and runtime on benchmark datasets for image segmentation. Finally, we provide a new object-tracking algorithm based on GridShift and show promising results for object tracking compared to CamShift and meanshift++.

Published
2022

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