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3. Riesgo de aparición de segundas neoplasias cutáneas en una cohorte de pacientes diagnosticados de carcinoma queratinocítico (carcinoma basocelular y carcinoma epidermoide) tratados con cirugía de Mohs. Estudio de cohortes prospectivo nacional

Author

R. Miñano Medrano, J.L. López Estebaranz, O. Sanmartin-Jiménez, J.R. Garcés, M.A. Rodríguez-Prieto, E. Vilarrasa-Rull, E. de Eusebio-Murillo, B. Escutia-Muñoz, Á. Flórez-Menéndez, J.L. Artola-Igarza, A. Alfaro-Rubio, P. Redondo, Y. Delgado-Jiménez, J.M. Sánchez-Schmidt, I. Allende-Markixana, M.L. Alonso-Pacheco, B. García-Bracamonte, P. de la Cueva-Dobao, R. Navarro-Tejedor, C. Ciudad-Blanco, L. Carnero-González, H. Vázquez-Veiga, N. Cano-Martínez, V. Ruiz-Salas, P. Sánchez-Sambucety, R. Botella-Estrada, B. González-Sixto, A. Martorell-Calatayud, P. Gil, V. Morales-Gordillo, A. Toll-Abelló, I. Ocerin-Guerra, M. Mayor-Arenal, R. Suárez-Fernández, L. Sainz-Gaspar, M.A. Descalzo, and I. García-Doval

Subjects
Mohs micrographic surgery, Basal cell carcinoma, Squamous cell carcinoma, Second cancer, Incidence, Risk factors, Dermatology, RL1-803, Internal medicine, RC31-1245
Abstract

Resumen: Objetivo: Los pacientes diagnosticados de cáncer queratinocítico (carcinoma basocelular y carcinoma epidermoide cutáneo) o cáncer cutáneo no melanoma (CCNM) tienen un riesgo aumentado de desarrollar una segunda neoplasia cutánea. Nuestro objetivo es describir la frecuencia, tasa de incidencia y factores de riesgo predisponentes para desarrollar una segunda neoplasia cutánea en una cohorte de pacientes tratados mediante cirugía micrográfica de Mohs (CMM). Material y métodos: Estudio prospectivo de una cohorte nacional de pacientes incluidos para realización de CMM para tratar CCNM en 22 centros españoles (julio 2013-febrero 2020) REGESMOHS. Las variables analizadas incluyen las características demográficas, la frecuencia de aparición de segundas neoplasias cutáneas, sus tasas de incidencia y factores de riesgo, y se estimaron utilizando un modelo de regresión logístico multivariante de efectos mixtos. Resultados: Fueron intervenidos 4.768 pacientes: 4.397 (92%) carcinomas basocelulares, y 371 (8%) carcinomas epidermoides. El tiempo medio de seguimiento fue de 2,4 años. Se diagnosticó un nuevo tumor durante el seguimiento en 1.201 pacientes (25%); 1.013 (21%) fueron carcinomas basocelulares, 154 (3%) carcinomas epidermoides cutáneos, 20 melanomas (0,4%) La tasa de incidencia fue de 107 (101-113) por 1.000 personas/año para cualquier tumor; 90 (85-96) para el carcinoma basocelular, 14 (12-16) para el carcinoma epidermoide cutáneo y 2 (1-3) para el melanoma. El riesgo de nueva neoplasia fue mayor en varones que en mujeres 738 (61%) vs. 463 (39%). Los factores de riesgo más significativos fueron la historia de múltiples tumores previos al diagnóstico (RR: 4,6; IC 95%: 2,9-7,1); la inmunosupresión (RR: 2,1; IC 95%: 1,4-3,1) y paciente varón (RR: 1,6; IC 95%: 1,4-1,9). Conclusión: Los pacientes diagnosticados de cáncer queratinocítico intervenido mediante cirugía de Mohs tienen un riesgo aumentado de aparición de segundas neoplasias, sobre todo en aquellos pacientes con historia de tumores múltiples al diagnóstico, inmunodeprimidos y varones. Abstract: Objective: Patients with nonmelanoma skin cancer (NMSC)—ie, basal cell carcinoma (BCC) or squamous cell carcinoma (SCC)—have an increased risk of developing a second skin cancer. The aim of this study was to describe the frequency, incidence per 1000 person-years, and predictors of a second skin cancer in a cohort of patients with NMSC treated with Mohs micrographic surgery (MMS). Material and methods: Prospective study of a national cohort of patients with NMSC who underwent MMS at 22 Spanish hospitals between July 2013 and February 2020; case data were recorded in the REGESMOHS registry. The study variables included demographic characteristics, frequency and incidence per 1000 person-years of second skin cancers diagnosed during the study period, and risk factors identified using mixed-effects logistic regression. Results: We analyzed data for 4768 patients who underwent MMS; 4397 (92%) had BCC and 371 (8%) had SCC. Mean follow-up was 2.4 years. Overall, 1201 patients (25%) developed a second skin cancer during follow-up; 1013 of the tumors were BCCs (21%), 154 were SCCs (3%), and 20 were melanomas (0.4%). The incidence was 107 per 1000 person-years (95% CI, 101-113) for any cancer, 90 per 1000 person-years (95% CI, 85-96) for BCC, 14 (95% CI, 12-16) per 1000 person-years for SCC, and 2 (95% CI, 1-3) per 1000 person-years for melanoma. More men than women developed a subsequent skin cancer (738 [61%] vs 463 [39%]). The main risk factors were a history of multiple tumors before diagnosis (relative risk [RR], 4.6; 95% CI, 2.9-7.1), immunosuppression (RR, 2.1; 95% CI, 1.4-3.1), and male sex (RR, 1.6; 95% CI, 1.4-1.9). Conclusion: Patients have an increased risk of developing a second tumor after MMS treatment of NMSC. Risk factors are a history of multiple tumors at diagnosis, immunosuppression, and male sex.

Published
2022
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4. Inteligencia artificial en dermatología: ¿amenaza u oportunidad?

Author

A. Martorell, A. Martin-Gorgojo, E. Ríos-Viñuela, J.M. Rueda-Carnero, F. Alfageme, and R. Taberner

Subjects
Artificial intelligence, Health, Oncology, Aesthetics, Inflammation, Dermatopathology, Dermatology, RL1-803, Internal medicine, RC31-1245
Abstract

Resumen: La irrupción de la inteligencia artificial (IA) a nivel mundial ha supuesto un antes y un después en nuestras vidas, generando grandes mejoras en diferentes sectores, como el de la automoción y el agroalimentario, entre otros, lo que ha llevado a denominarla la cuarta revolución industrial. La AI, capaz de aprender de forma automatizada y de ayudar al profesional a mejorar sus procesos, promete cambiar el ámbito sanitario tal y como lo conocemos mediante: 1) aplicaciones capaces de generar salud en la población general a partir del uso de información de calidad y de segmentación de consejos basados en modelos de predicción; 2) modelos capaces de generar algoritmos de predicción a partir de datos anonimizados procedentes de información clínica, a fin de mejorar la prevención primaria; 3) sistemas de análisis de imagen capaces de dar a los profesionales de la salud un soporte extra en la toma de decisiones, mejorando la prevención secundaria; y 4) aplicación de robótica combinada en la mejora de procesos ligados al ámbito de salud y bienestar.Sin embargo, la falta de conocimiento tanto en este tipo de tecnología, como en los términos y la metodología de validación de la misma, hace que la clase médica dude en si esta revolución supone una amenaza o una oportunidad para la profesión. En el presente artículo de revisión pretendemos introducir una serie de aspectos básicos de la IA aplicada a la dermatología, así como los principales avances sucedidos en este campo en los últimos 5 años. Abstract: The worldwide explosion of interest in artificial intelligence (AI) has created a before-and-after moment in our lives by generating great improvements in such sectors as the automotive and food production industries. AI has even been called the fourth industrial revolution. Machine learning through AI is helping to improve professional processes and promises to transform the health care sector as we know it in various ways: 1) through applications able to promote health in the general population by providing high-quality information and offering advice for different segments of the population based on prediction models; 2) by developing prediction models based on anonymized clinical data, for preventive purposes in primary care; 3) by analyzing images to provide additional decision-making support for health care providers, for improving specialist care at the secondary level; and 4) through robotics applied to processes that promote health and well-being. However, the medical profession harbors doubts about whether this revolution is a threat or an opportunity owing to a lack of understanding of AI technology and the methods used to validate its applications. This article outlines basic aspects of AI as it is applied in dermatology and reviews the main advances achieved in the last 5 years.

Published
2022
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5. Observation of the open-charm tetraquark state $T_{cs 0}^{*}(2870)^0$ in the $B^- \rightarrow D^- D^0 K_\mathrm{S}^0$ decay

Author

LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Balboni, A., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. A., Belin, S., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bonacci, R. B., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonaura, A., Buonincontri, L., Burke, A. T., Burr, C., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., Caillet, A. C., Calabrese, R., Ramirez, S. Calderon, Calefice, L., Cali, S., Calvi, M., Gomez, M. Calvo, Magalhaes, P. Camargo, Bouzas, J. I. Cambon, Campana, P., Perez, D. H. Campora, Quezada, A. F. Campoverde, Capelli, S., Capriotti, L., Caravaca-Mora, R., Carbone, A., Salgado, L. Carcedo, Cardinale, R., Cardini, A., Carniti, P., Carus, L., Vidal, A. Casais, Caspary, R., Casse, G., Cattaneo, M., Cavallero, G., Cavallini, V., Celani, S., Cervenkov, D., Cesare, S., Chadwick, A. J., Chahrour, I., Charles, M., Charpentier, Ph., Chatzianagnostou, E., Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., Chiotopoulos, X., Chobanova, V., Cholak, S., Chrzaszcz, M., Chubykin, A., Chulikov, V., Ciambrone, P., Vidal, X. Cid, Ciezarek, G., Cifra, P., Clarke, P. E. L., Clemencic, M., Cliff, H. V., Closier, J., Toapaxi, C. Cocha, Coco, V., Cogan, J., Cogneras, E., Cojocariu, L., Collaviti, S., Collins, P., Colombo, T., Colonna, M., Comerma-Montells, A., Congedo, L., Contu, A., Cooke, N., Corredoira, I., Correia, A., Corti, G., Meldrum, J. J. Cottee, Couturier, B., Craik, D. C., Torres, M. Cruz, Rivera, E. Curras, Currie, R., Da Silva, C. L., Dadabaev, S., Dai, L., Dai, X., Dall'Occo, E., Dalseno, J., D'Ambrosio, C., Daniel, J., Danilina, A., d'Argent, P., Darze, G., Davidson, A., Davies, J. E., Davis, A., Francisco, O. De Aguiar, De Angelis, C., De Benedetti, F., de Boer, J., De Bruyn, K., De Capua, S., De Cian, M., Da Graca, U. De Freitas Carneiro, De Lucia, E., De Miranda, J. M., De Paula, L., De Serio, M., De Simone, P., De Vellis, F., de Vries, J. A., Debernardis, F., Decamp, D., Dedu, V., Dekkers, S., Del Buono, L., Delaney, B., Dembinski, H. -P., Deng, J., Denysenko, V., Deschamps, O., Dettori, F., Dey, B., Di Nezza, P., Diachkov, I., Didenko, S., Ding, S., Dittmann, L., Dobishuk, V., Docheva, A. D., Dong, C., Donohoe, A. M., Dordei, F., Reis, A. C. dos, Dowling, A. D., Duan, W., Duda, P., Dudek, M. W., Dufour, L., Duk, V., Durante, P., Duras, M. M., Durham, J. M., Durmus, O. D., Dziurda, A., Dzyuba, A., Easo, S., Eckstein, E., Egede, U., Egorychev, A., Egorychev, V., Eisenhardt, S., Ejopu, E., Eklund, L., Elashri, M., Ellbracht, J., Ely, S., Ene, A., Eschle, J., Esen, S., Evans, T., Fabiano, F., Falcao, L. N., Fan, Y., Fang, B., Fantini, L., Faria, M., Farmer, K., Fazzini, D., Felkowski, L., Feng, M., Feo, M., Casani, A. Fernandez, Gomez, M. Fernandez, Fernez, A. D., Ferrari, F., Rodrigues, F. Ferreira, Ferrillo, M., Ferro-Luzzi, M., Filippov, S., Fini, R. A., Fiorini, M., Firlej, M., Fischer, K. L., Fitzgerald, D. S., Fitzpatrick, C., Fiutowski, T., Fleuret, F., Fontana, M., Foreman, L. F., Forty, R., Foulds-Holt, D., Lima, V. Franco, Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Frei, C., Friday, D. A., Fu, J., Führing, Q., Fujii, Y., Fulghesu, T., Gabriel, E., Galati, G., Galati, M. D., Torreira, A. Gallas, Galli, D., Gambetta, S., Gandelman, M., Gandini, P., Ganie, B., Gao, H., Gao, R., Gao, T. Q., Gao, Y., Martin, L. M. Garcia, Moreno, P. Garcia, Pardiñas, J. García, Gardner, P., Garg, K. G., Garrido, L., Gaspar, C., Geertsema, R. E., Gerken, L. L., Gersabeck, E., Gersabeck, M., Gershon, T., Ghizzo, S., Ghorbanimoghaddam, Z., Giambastiani, L., Giasemis, F. I., Gibson, V., Giemza, H. K., Gilman, A. L., Giovannetti, M., Gioventù, A., Girardey, L., Gironell, P. Gironella, Giugliano, C., Giza, M. A., Gkougkousis, E. L., Glaser, F. C., Gligorov, V. V., Göbel, C., Golobardes, E., Golubkov, D., Golutvin, A., Fernandez, S. Gomez, Gomulka, W., Abrantes, F. Goncalves, Goncerz, M., Gong, G., Gooding, J. A., Gorelov, I. V., Gotti, C., Grabowski, J. P., Cardoso, L. A. Granado, Graugés, E., Graverini, E., Grazette, L., Graziani, G., Grecu, A. T., Greeven, L. M., Grieser, N. A., Grillo, L., Gromov, S., Gu, C., Guarise, M., Guerry, L., Guittiere, M., Guliaeva, V., Günther, P. A., Guseinov, A. -K., Gushchin, E., Guz, Y., Gys, T., Habermann, K., Hadavizadeh, T., Hadjivasiliou, C., Haefeli, G., Haen, C., Hajheidari, M., Hallett, G., Halvorsen, M. M., Hamilton, P. M., Hammerich, J., Han, Q., Han, X., Hansmann-Menzemer, S., Hao, L., Harnew, N., Harris, T. H., Hartmann, M., Hashmi, S., He, J., Hemmer, F., Henderson, C., Henderson, R. D. L., Hennequin, A. M., Hennessy, K., Henry, L., Herd, J., Gascon, P. Herrero, Heuel, J., Hicheur, A., Mendizabal, G. Hijano, Horswill, J., Hou, R., Hou, Y., Howarth, N., Hu, J., Hu, W., Hu, X., Huang, W., Hulsbergen, W., Hunter, R. J., Hushchyn, M., Hutchcroft, D., Idzik, M., Ilin, D., Ilten, P., Inglessi, A., Iniukhin, A., Ishteev, A., Ivshin, K., Jacobsson, R., Jage, H., Elles, S. J. Jaimes, Jakobsen, S., Jans, E., Jashal, B. K., Jawahery, A., Jevtic, V., Jiang, E., Jiang, X., Jiang, Y., Jiang, Y. J., John, M., Rajan, A. John Rubesh, Johnson, D., Jones, C. R., Jones, T. P., Joshi, S., Jost, B., Castella, J. Juan, Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kane, M., Kang, Y., Kar, C., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., Kazanecki, M. K., Keizer, F., Kenzie, M., Ketel, T., Khanji, B., Kharisova, A., Kholodenko, S., Khreich, G., Kirn, T., Kirsebom, V. S., Kitouni, O., Klaver, S., Kleijne, N., Klimaszewski, K., Kmiec, M. R., Koliiev, S., Kolk, L., Konoplyannikov, A., Kopciewicz, P., Koppenburg, P., Korolev, M., Kostiuk, I., Kot, O., Kotriakhova, S., Kozachuk, A., Kravchenko, P., Kravchuk, L., Kreps, M., Krokovny, P., Krupa, W., Krzemien, W., Kshyvanskyi, O., Kubis, S., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Gonzalez, P. Laguarta, Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Lanfranchi, G., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. Le, Lee, H., Lefèvre, R., Leflat, A., Legotin, S., Lehuraux, M., Cid, E. Lemos, Leroy, O., Lesiak, T., Lesser, E. D., Leverington, B., Li, A., Li, C., Li, H., Li, K., Li, L., Li, M., Li, P., Li, P. -R., Li, Q., Li, S., Li, T., Li, Y., Lian, Z., Liang, X., Libralon, S., Lin, C., Lin, T., Lindner, R., Linton, H., Lisovskyi, V., Litvinov, R., Liu, F. L., Liu, G., Liu, K., Liu, S., Liu, W., Liu, Y., Liu, Y. L., Salvia, A. Lobo, Loi, A., Long, T., Lopes, J. H., Huertas, A. Lopez, Soliño, S. López, Lu, Q., Lucarelli, C., Lucchesi, D., Martinez, M. Lucio, Lukashenko, V., Luo, Y., Lupato, A., Luppi, E., Lynch, K., Lyu, X. -R., Ma, G. M., Maccolini, S., Machefert, F., Maciuc, F., Mack, B., Mackay, I., Mackey, L. M., Mohan, L. R. Madhan, Madurai, M. J., Maevskiy, A., Magdalinski, D., Maisuzenko, D., Majewski, M. W., Malczewski, J. J., Malde, S., Malentacca, L., Malinin, A., Maltsev, T., Manca, G., Mancinelli, G., Mancuso, C., Escalero, R. Manera, Manganella, F. M., Manuzzi, D., Marangotto, D., Marchand, J. F., Marchevski, R., Marconi, U., Mariani, E., Mariani, S., Benito, C. Marin, Marks, J., Marshall, A. M., Martel, L., Martelli, G., Martellotti, G., Martinazzoli, L., Martinelli, M., Gomez, D. Martinez, Santos, D. Martinez, Vidal, F. Martinez, Granollers, A. Martorell i, Massafferri, A., Matev, R., Mathad, A., Matiunin, V., Matteuzzi, C., Mattioli, K. R., Mauri, A., Maurice, E., Mauricio, J., Mayencourt, P., de Cos, J. Mazorra, Mazurek, M., McCann, M., Mcconnell, L., McGrath, T. H., McHugh, N. T., McNab, A., McNulty, R., Meadows, B., Meier, G., Melnychuk, D., Meng, F. M., Merk, M., Merli, A., Garcia, L. Meyer, Miao, D., Miao, H., Mikhasenko, M., Milanes, D. A., Minotti, A., Minucci, E., Miralles, T., Mitreska, B., Mitzel, D. S., Modak, A., Mohammed, R. A., Moise, R. D., Mokhnenko, S., Cardenas, E. F. Molina, Mombächer, T., Monk, M., Monteil, S., Gomez, A. Morcillo, Morello, G., Morello, M. J., Morgenthaler, M. P., Moron, J., Morren, W., Morris, A. B., Morris, A. G., Mountain, R., Mu, H., Mu, Z. M., Muhammad, E., Muheim, F., Mulder, M., Müller, K., Muñoz-Rojas, F., Murta, R., Naik, P., Nakada, T., Nandakumar, R., Nanut, T., Nasteva, I., Needham, M., Neri, N., Neubert, S., Neufeld, N., Neustroev, P., Nicolini, J., Nicotra, D., Niel, E. M., Nikitin, N., Niu, Q., Nogarolli, P., Nogga, P., Normand, C., Fernandez, J. Novoa, Nowak, G., Nunez, C., Nur, H. N., Oblakowska-Mucha, A., Obraztsov, V., Oeser, T., Okamura, S., Okhotnikov, A., Okhrimenko, O., Oldeman, R., Oliva, F., Olocco, M., Onderwater, C. J. G., O'Neil, R. H., Osthues, D., Goicochea, J. M. Otalora, Owen, P., Oyanguren, A., Ozcelik, O., Paciolla, F., Padee, A., Padeken, K. O., Pagare, B., Pais, P. R., Pajero, T., Palano, A., Palutan, M., Pan, X., Panshin, G., Paolucci, L., Papanestis, A., Pappagallo, M., Pappalardo, L. L., Pappenheimer, C., Parkes, C., Parmar, D., Passalacqua, B., Passaleva, G., Passaro, D., Pastore, A., Patel, M., Patoc, J., Patrignani, C., Paul, A., Pawley, C. J., Pellegrino, A., Peng, J., Altarelli, M. Pepe, Perazzini, S., Pereima, D., Da Costa, H. Pereira, Castro, A. Pereiro, Perret, P., Perrevoort, A., Perro, A., Peters, M. J., Petridis, K., Petrolini, A., Pfaller, J. P., Pham, H., Pica, L., Piccini, M., Piccolo, L., Pietrzyk, B., Pietrzyk, G., Pinci, D., Pisani, F., Pizzichemi, M., Placinta, V., Casasus, M. Plo, Poeschl, T., Polci, F., Lener, M. Poli, Poluektov, A., Polukhina, N., Polyakov, I., Polycarpo, E., Ponce, S., Popov, D., Poslavskii, S., Prasanth, K., Prouve, C., Provenzano, D., Pugatch, V., Punzi, G., Qasim, S., Qian, Q. Q., Qian, W., Qin, N., Qu, S., Quagliani, R., Trejo, R. I. Rabadan, Rademacker, J. H., Rama, M., García, M. Ramírez, De Oliveira, V. Ramos, Pernas, M. Ramos, Rangel, M. S., Ratnikov, F., Raven, G., De Miguel, M. Rebollo, Redi, F., Reich, J., Reiss, F., Ren, Z., Resmi, P. K., Ribatti, R., Ricart, G. R., Riccardi, D., Ricciardi, S., Richardson, K., Richardson-Slipper, M., Rinnert, K., Robbe, P., Robertson, G., Rodrigues, E., Alvarez, A. Rodriguez, Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Rodriguez, E. Rodriguez, Roensch, J., Rogachev, A., Rogovskiy, A., Rolf, D. L., Roloff, P., Romanovskiy, V., Vidal, A. Romero, Romolini, G., Ronchetti, F., Rong, T., Rotondo, M., Roy, S. R., Rudolph, M. S., Diaz, M. Ruiz, Fernandez, R. A. Ruiz, Vidal, J. Ruiz, Ryzhikov, A., Ryzka, J., Saavedra-Arias, J. J., Silva, J. J. Saborido, Sadek, R., Sagidova, N., Sahoo, D., Sahoo, N., Saitta, B., Salomoni, M., Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santoro, L., Santovetti, E., Saputi, A., Saranin, D., Sarnatskiy, A., Sarpis, G., Sarpis, M., Satriano, C., Satta, A., Saur, M., Savrina, D., Sazak, H., Sborzacchi, F., Smead, L. G. 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Subjects
High Energy Physics - Experiment
Abstract

An amplitude analysis of $B^-\rightarrow D^- D^0 K_\mathrm{S}^0$ decays is performed using proton-proton collision data, corresponding to an integrated luminosity of $9\,\text{fb}^{-1}$, collected with the LHCb detector at center-of-mass energies of 7, 8, and 13$\mathrm{\,Te\kern -0.1em V}$. A resonant structure of spin-parity $0^+$ is observed in the $D^0 K_\mathrm{S}^0$ invariant-mass spectrum with a significance of $5.3\,\sigma$. The mass and width of the state, modeled with a Breit$-$Wigner lineshape, are determined to be $2883\pm11\pm6\mathrm{\,Me\kern -0.1em V\!/}c^2$ and $87_{-47}^{+22}\pm6\mathrm{\,Me\kern -0.1em V}$ respectively, where the first uncertainties are statistical and the second systematic. These properties and the quark content are consistent with those of the open-charm tetraquark state $T_{cs 0}^{*}(2870)^0$ observed previously in the $D^+ K^-$ final state of the $B^-\rightarrow D^- D^+ K^-$ decay. This result confirms the existence of the $T_{cs 0}^{*}(2870)^0$ state in a new decay mode. The $T_{cs1}^{*}(2900)^0$ state, reported in the $B^-\rightarrow D^- D^+ K^-$ decay, is also searched for in the $D^0 K_\mathrm{S}^0$ invariant-mass spectrum of the $B^- \rightarrow D^- D^0 K_\mathrm{S}^0$ decay, without finding evidence for it., Comment: All figures and tables, along with machine-readable versions and any supplementary material and information, are available at https://lbfence.cern.ch/alcm/public/analysis/full-details/3162/ (LHCb public pages)

Published
2024

6. Study of $\it{\Lambda}_{\it{b}}^\rm{0}$ and $\it{\Xi}_{\it{b}}^\rm{0}$ decays to $\it{\Lambda} h^+h^{'-}$ and evidence for $CP$ violation in $\it{\Lambda}_{\it{b}}^\rm{0}\to\it{\Lambda} K^+K^-$ decays

Author

LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Balboni, A., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. A., Belin, S., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bonacci, R. B., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonaura, A., Buonincontri, L., Burke, A. T., Burr, C., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., Caillet, A. C., Calabrese, R., Ramirez, S. Calderon, Calefice, L., Cali, S., Calvi, M., Gomez, M. Calvo, Magalhaes, P. Camargo, Bouzas, J. I. Cambon, Campana, P., Perez, D. H. Campora, Quezada, A. F. Campoverde, Capelli, S., Capriotti, L., Caravaca-Mora, R., Carbone, A., Salgado, L. Carcedo, Cardinale, R., Cardini, A., Carniti, P., Carus, L., Vidal, A. Casais, Caspary, R., Casse, G., Cattaneo, M., Cavallero, G., Cavallini, V., Celani, S., Cervenkov, D., Cesare, S., Chadwick, A. J., Chahrour, I., Charles, M., Charpentier, Ph., Chatzianagnostou, E., Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., Chiotopoulos, X., Chobanova, V., Cholak, S., Chrzaszcz, M., Chubykin, A., Chulikov, V., Ciambrone, P., Vidal, X. Cid, Ciezarek, G., Cifra, P., Clarke, P. E. L., Clemencic, M., Cliff, H. V., Closier, J., Toapaxi, C. 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John Rubesh, Johnson, D., Jones, C. R., Jones, T. P., Joshi, S., Jost, B., Castella, J. Juan, Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kane, M., Kang, Y., Kar, C., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., Kazanecki, M. K., Keizer, F., Kenzie, M., Ketel, T., Khanji, B., Kharisova, A., Kholodenko, S., Khreich, G., Kirn, T., Kirsebom, V. S., Kitouni, O., Klaver, S., Kleijne, N., Klimaszewski, K., Kmiec, M. R., Koliiev, S., Kolk, L., Konoplyannikov, A., Kopciewicz, P., Koppenburg, P., Korolev, M., Kostiuk, I., Kot, O., Kotriakhova, S., Kozachuk, A., Kravchenko, P., Kravchuk, L., Kreps, M., Krokovny, P., Krupa, W., Krzemien, W., Kshyvanskyi, O., Kubis, S., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Gonzalez, P. Laguarta, Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Lanfranchi, G., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. 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Subjects
High Energy Physics - Experiment
Abstract

A study of $\it{\Lambda}_{\it{b}}^\rm{0}$ and $\it{\Xi}_{\it{b}}^\rm{0}$ decays to $\it{\Lambda} h^{+} h^{\prime -}$ $(h^{(\prime)}=\pi, K)$ is performed using $pp$ collision data collected by the LHCb experiment during LHC Runs 1$-$2, corresponding to an integrated luminosity of $9~\rm{fb}^{-1}$. The branching fractions for these decays are measured using the $\it{\Lambda}_{\it{b}}^\rm{0}\to\it{\Lambda}_{\it{c}}^+(\to\it{\Lambda}\pi^+)\pi^-$ decay as control channel. The decays $\it{\Lambda}_{\it{b}}^\rm{0}\to\it{\Lambda}\pi^+\pi^-$ and $\it{\Xi}_{\it{b}}^\rm{0}\to\it{\Lambda}K^-\pi^+$ are observed for the first time. For decay modes with sufficient signal yields, $CP$ asymmetries are measured in the full and localized regions of the final-state phase space. Evidence is found for $CP$ violation in the $\it{\Lambda}_{\it{b}}^\rm{0}\to\it{\Lambda}K^+K^-$ decay, interpreted as originating primarily from an asymmetric $\it{\Lambda}_{\it{b}}^\rm{0} \to \it{N}^{*+} \it{K}^-$ decay amplitude. The measured $CP$ asymmetries for the other decays are compatible with zero., Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2024-043.html (LHCb public pages)

Published
2024

7. First evidence for direct CP violation in beauty to charmonium decays

Author

LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Balboni, A., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. A., Belin, S., Bellee, V., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bonacci, R. B., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonaura, A., Buonincontri, L., Burke, A. T., Burr, C., Butter, J. 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Subjects
High Energy Physics - Experiment
Abstract

The $C\!P$ asymmetry and branching fraction of the CKM-suppressed decay $B^+\!\to J\mskip -3mu/\mskip -2mu\psi\,\pi^+$ are precisely measured relative to the favoured decay $B^+\!\to J\mskip -3mu/\mskip -2mu\psi\,K^+$, using a sample of proton-proton collision data corresponding to an integrated luminosity of $5.4~\mathrm{fb}^{-1}$ recorded at center-of-mass energy of $13~\mathrm{TeV}$ during 2016--2018. The results of the $C\!P$ asymmetry difference and branching fraction ratio are \begin{align*} \Delta\mathcal{A}^{C\!P} &\equiv \mathcal{A}^{C\!P}(B^+ \to J\mskip -3mu/\mskip -2mu\psi\,\pi^+) - \mathcal{A}^{C\!P}(B^+ \to J\mskip -3mu/\mskip -2mu\psi\,K^+) = (1.29 \pm 0.49 \pm 0.08) \times 10^{-2}, \end{align*} \begin{equation*} \mathcal{R}_{\pi/K} \equiv \frac{\mathcal{B}(B^+ \!\to J\mskip -3mu/\mskip -2mu\psi\,\pi^+)}{\mathcal{B}(B^+ \!\to J\mskip -3mu/\mskip -2mu\psi\,K^+)} = (3.852 \pm 0.022 \pm 0.018) \times 10^{-2}. \end{equation*} where the first uncertainties are statistical and the second systematic. A combination with previous LHCb results based on data collected at $7$ and $8~\mathrm{TeV}$ in 2011 and 2012 yields $\Delta\mathcal{A}^{C\!P} = (1.42 \pm 0.43 \pm 0.08) \times 10^{-2}$ and $\mathcal{R}_{\pi/K} = (3.846 \pm 0.018 \pm 0.018) \times 10^{-2}$. The combined $\Delta\mathcal{A}^{C\!P}$ value deviates from zero by 3.2 standard deviations, providing the first evidence for direct $C\!P$ violation in the amplitudes of beauty decays to charmonium final states., Comment: 18 pages, 2 figures, no conference or journal information All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lbfence.cern.ch/alcm/public/analysis/full-details/1623/ (LHCb public pages)

Published
2024

8. Measurement of $\phi(1020)$ meson production in fixed-target $\textit{p}$Ne collisions at $\sqrt{s_{NN}}$ = 68.5 GeV

Author

LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Balboni, A., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. A., Belin, S., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bonacci, R. B., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonaura, A., Buonincontri, L., Burke, A. T., Burr, C., Butter, J. 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Subjects
High Energy Physics - Experiment, Nuclear Experiment
Abstract

The first measurement of $\phi(1020)$ meson production in fixed-target $p$Ne collisions at $\sqrt{s_{NN}}=68.5$ GeV is presented. The $\phi(1020)$ mesons are reconstructed in their $K^{+}K^{-}$ decay in a data sample consisting of proton collisions on neon nuclei at rest, corresponding to an integrated luminosity of $21.7 \pm 1.4$ nb$^{-1}$, collected by the LHCb detector at CERN. The $\phi(1020)$ production cross-section in the centre-of-mass rapidity range of $-1.8

Published
2024

9. Measurement of the $\psi(2S)$ to $J/\psi$ cross-section ratio as a function of centrality in PbPb collisions at $\sqrt{s_{\text{NN}}}$ = 5.02 TeV

Author

LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Balboni, A., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. A., Belin, S., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bonacci, R. B., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonaura, A., Buonincontri, L., Burke, A. T., Burr, C., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., Caillet, A. C., Calabrese, R., Ramirez, S. Calderon, Calefice, L., Cali, S., Calvi, M., Gomez, M. Calvo, Magalhaes, P. Camargo, Bouzas, J. I. Cambon, Campana, P., Perez, D. H. Campora, Quezada, A. F. Campoverde, Capelli, S., Capriotti, L., Caravaca-Mora, R., Carbone, A., Salgado, L. Carcedo, Cardinale, R., Cardini, A., Carniti, P., Carus, L., Vidal, A. Casais, Caspary, R., Casse, G., Cattaneo, M., Cavallero, G., Cavallini, V., Celani, S., Cervenkov, D., Cesare, S., Chadwick, A. J., Chahrour, I., Charles, M., Charpentier, Ph., Chatzianagnostou, E., Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., Chiotopoulos, X., Chobanova, V., Cholak, S., Chrzaszcz, M., Chubykin, A., Chulikov, V., Ciambrone, P., Vidal, X. Cid, Ciezarek, G., Cifra, P., Clarke, P. E. L., Clemencic, M., Cliff, H. V., Closier, J., Toapaxi, C. 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John Rubesh, Johnson, D., Jones, C. R., Jones, T. P., Joshi, S., Jost, B., Castella, J. Juan, Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kane, M., Kang, Y., Kar, C., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., Kazanecki, M. K., Keizer, F., Kenzie, M., Ketel, T., Khanji, B., Kharisova, A., Kholodenko, S., Khreich, G., Kirn, T., Kirsebom, V. S., Kitouni, O., Klaver, S., Kleijne, N., Klimaszewski, K., Kmiec, M. R., Koliiev, S., Kolk, L., Konoplyannikov, A., Kopciewicz, P., Koppenburg, P., Korolev, M., Kostiuk, I., Kot, O., Kotriakhova, S., Kozachuk, A., Kravchenko, P., Kravchuk, L., Kreps, M., Krokovny, P., Krupa, W., Krzemien, W., Kshyvanskyi, O., Kubis, S., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Gonzalez, P. Laguarta, Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Lanfranchi, G., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. 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P., Moron, J., Morren, W., Morris, A. B., Morris, A. G., Mountain, R., Mu, H., Mu, Z. M., Muhammad, E., Muheim, F., Mulder, M., Müller, K., Muñoz-Rojas, F., Murta, R., Naik, P., Nakada, T., Nandakumar, R., Nanut, T., Nasteva, I., Needham, M., Neri, N., Neubert, S., Neufeld, N., Neustroev, P., Nicolini, J., Nicotra, D., Niel, E. M., Nikitin, N., Niu, Q., Nogarolli, P., Nogga, P., Normand, C., Fernandez, J. Novoa, Nowak, G., Nunez, C., Nur, H. N., Oblakowska-Mucha, A., Obraztsov, V., Oeser, T., Okamura, S., Okhotnikov, A., Okhrimenko, O., Oldeman, R., Oliva, F., Olocco, M., Onderwater, C. J. G., O'Neil, R. H., Osthues, D., Goicochea, J. M. Otalora, Owen, P., Oyanguren, A., Ozcelik, O., Paciolla, F., Padee, A., Padeken, K. O., Pagare, B., Pais, P. R., Pajero, T., Palano, A., Palutan, M., Pan, X., Panshin, G., Paolucci, L., Papanestis, A., Pappagallo, M., Pappalardo, L. L., Pappenheimer, C., Parkes, C., Parmar, D., Passalacqua, B., Passaleva, G., Passaro, D., Pastore, A., Patel, M., Patoc, J., Patrignani, C., Paul, A., Pawley, C. J., Pellegrino, A., Peng, J., Altarelli, M. Pepe, Perazzini, S., Pereima, D., Da Costa, H. Pereira, Castro, A. Pereiro, Perret, P., Perrevoort, A., Perro, A., Peters, M. J., Petridis, K., Petrolini, A., Pfaller, J. P., Pham, H., Pica, L., Piccini, M., Piccolo, L., Pietrzyk, B., Pietrzyk, G., Pinci, D., Pisani, F., Pizzichemi, M., Placinta, V., Casasus, M. Plo, Poeschl, T., Polci, F., Lener, M. Poli, Poluektov, A., Polukhina, N., Polyakov, I., Polycarpo, E., Ponce, S., Popov, D., Poslavskii, S., Prasanth, K., Prouve, C., Provenzano, D., Pugatch, V., Punzi, G., Qasim, S., Qian, Q. Q., Qian, W., Qin, N., Qu, S., Quagliani, R., Trejo, R. I. Rabadan, Rademacker, J. H., Rama, M., García, M. Ramírez, De Oliveira, V. Ramos, Pernas, M. Ramos, Rangel, M. S., Ratnikov, F., Raven, G., De Miguel, M. Rebollo, Redi, F., Reich, J., Reiss, F., Ren, Z., Resmi, P. K., Ribatti, R., Ricart, G. R., Riccardi, D., Ricciardi, S., Richardson, K., Richardson-Slipper, M., Rinnert, K., Robbe, P., Robertson, G., Rodrigues, E., Alvarez, A. Rodriguez, Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Rodriguez, E. Rodriguez, Roensch, J., Rogachev, A., Rogovskiy, A., Rolf, D. L., Roloff, P., Romanovskiy, V., Vidal, A. Romero, Romolini, G., Ronchetti, F., Rong, T., Rotondo, M., Roy, S. R., Rudolph, M. S., Diaz, M. Ruiz, Fernandez, R. A. Ruiz, Vidal, J. Ruiz, Ryzhikov, A., Ryzka, J., Saavedra-Arias, J. J., Silva, J. J. Saborido, Sadek, R., Sagidova, N., Sahoo, D., Sahoo, N., Saitta, B., Salomoni, M., Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santoro, L., Santovetti, E., Saputi, A., Saranin, D., Sarnatskiy, A., Sarpis, G., Sarpis, M., Satriano, C., Satta, A., Saur, M., Savrina, D., Sazak, H., Sborzacchi, F., Smead, L. G. Scantlebury, Scarabotto, A., Schael, S., Scherl, S., Schiller, M., Schindler, H., Schmelling, M., Schmidt, B., Schmitt, S., Schmitz, H., Schneider, O., Schopper, A., Schulte, N., Schulte, S., Schune, M. H., Schwemmer, R., Schwering, G., Sciascia, B., Sciuccati, A., Segal, I., Sellam, S., Semennikov, A., Senger, T., Soares, M. Senghi, Sergi, A., Serra, N., Sestini, L., Seuthe, A., Shang, Y., Shangase, D. M., Shapkin, M., Sharma, R. S., Shchemerov, I., Shchutska, L., Shears, T., Shekhtman, L., Shen, Z., Sheng, S., Shevchenko, V., Shi, B., Shi, Q., Shimizu, Y., Shmanin, E., Shorkin, R., Shupperd, J. D., Coutinho, R. Silva, Simi, G., Simone, S., Skidmore, N., Skwarnicki, T., Slater, M. W., Smallwood, J. C., Smith, E., Smith, K., Smith, M., Snoch, A., Lavra, L. Soares, Sokoloff, M. D., Soler, F. J. P., Solomin, A., Solovev, A., Solovyev, I., Sommerfeld, N. S., Song, R., Song, Y., Song, Y. S., De Almeida, F. L. Souza, De Paula, B. Souza, Norella, E. Spadaro, Spedicato, E., Speer, J. 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Subjects
Nuclear Experiment, High Energy Physics - Experiment
Abstract

The dissociation of quarkonium states with different binding energies produced in heavy-ion collisions is a powerful probe for investigating the formation and properties of the quark-gluon plasma. The ratio of production cross-sections of $\psi(2S)$ and $J/\psi$ mesons times the ratio of their branching fractions into the dimuon final state is measured as a function of centrality using data collected by the LHCb detector in PbPb collisions at $\sqrt{s_{\text{NN}}}$ = 5.02 TeV. The measured ratio shows no dependence on the collision centrality, and is compared to the latest theory predictions and to the recent measurements in literature., Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2024-041.html (LHCb public pages)

Published
2024

10. The role of expansion strategies and operational attributes on hotel performance: a compositional approach

Author

Mulet-Forteza, Carles, Ferrer-Rosell, Berta, Cunill, Onofre Martorell, and Linares-Mustarós, Salvador

Subjects
Economics - Econometrics
Abstract

This study aims to explore the impact of expansion strategies and specific attributes of hotel establishments on the performance of international hotel chains, focusing on four key performance indicators: RevPAR, efficiency, occupancy, and asset turnover. Data were collected from 255 hotels across various international hotel chains, providing a comprehensive assessment of how different expansion strategies and hotel attributes influence performance. The research employs compositional data analysis (CoDA) to address the methodological limitations of traditional financial ratios in statistical analysis. The findings indicate that ownership-based expansion strategies result in higher operational performance, as measured by revenue per available room, but yield lower economic performance due to the high capital investment required. Non-ownership strategies, such as management contracts and franchising, show superior economic efficiency, offering more flexibility and reduced financial risk. This study contributes to the hospitality management literature by applying CoDA, a novel methodological approach in this field, to examine the performance of different hotel expansion strategies with a sound and more appropriate method. The insights provided can guide hotel managers and investors in making informed decisions to optimize both operational and economic performance., Comment: 21 pages

Published
2024

11. Study of $D_{s1}(2460)^{+}\to D_{s}^{+}\pi^{+}\pi^{-}$ in $B\to {\bar{D}}^{(*)}D_{s}^{+}\pi^{+}\pi^{-}$ decays

Author

LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Balboni, A., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. A., Belin, S., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bonacci, R. B., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonaura, A., Buonincontri, L., Burke, A. T., Burr, C., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., Caillet, A. C., Calabrese, R., Ramirez, S. Calderon, Calefice, L., Cali, S., Calvi, M., Gomez, M. Calvo, Magalhaes, P. Camargo, Bouzas, J. I. Cambon, Campana, P., Perez, D. H. Campora, Quezada, A. F. Campoverde, Capelli, S., Capriotti, L., Caravaca-Mora, R., Carbone, A., Salgado, L. Carcedo, Cardinale, R., Cardini, A., Carniti, P., Carus, L., Vidal, A. Casais, Caspary, R., Casse, G., Cattaneo, M., Cavallero, G., Cavallini, V., Celani, S., Cervenkov, D., Cesare, S., Chadwick, A. J., Chahrour, I., Charles, M., Charpentier, Ph., Chatzianagnostou, E., Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., Chiotopoulos, X., Chobanova, V., Cholak, S., Chrzaszcz, M., Chubykin, A., Chulikov, V., Ciambrone, P., Vidal, X. Cid, Ciezarek, G., Cifra, P., Clarke, P. E. L., Clemencic, M., Cliff, H. V., Closier, J., Toapaxi, C. Cocha, Coco, V., Cogan, J., Cogneras, E., Cojocariu, L., Collaviti, S., Collins, P., Colombo, T., Colonna, M. C., Comerma-Montells, A., Congedo, L., Contu, A., Cooke, N., Corredoira, I., Correia, A., Corti, G., Meldrum, J. J. Cottee, Couturier, B., Craik, D. C., Torres, M. Cruz, Rivera, E. Curras, Currie, R., Da Silva, C. L., Dadabaev, S., Dai, L., Dai, X., Dall'Occo, E., Dalseno, J., D'Ambrosio, C., Daniel, J., Danilina, A., d'Argent, P., Davidson, A., Davies, J. E., Davis, A., Francisco, O. De Aguiar, De Angelis, C., De Benedetti, F., de Boer, J., De Bruyn, K., De Capua, S., De Cian, M., Da Graca, U. De Freitas Carneiro, De Lucia, E., De Miranda, J. M., De Paula, L., De Serio, M., De Simone, P., De Vellis, F., de Vries, J. A., Debernardis, F., Decamp, D., Dedu, V., Dekkers, S., Del Buono, L., Delaney, B., Dembinski, H. -P., Deng, J., Denysenko, V., Deschamps, O., Dettori, F., Dey, B., Di Nezza, P., Diachkov, I., Didenko, S., Ding, S., Dittmann, L., Dobishuk, V., Docheva, A. D., Dong, C., Donohoe, A. M., Dordei, F., Reis, A. C. dos, Dowling, A. D., Duan, W., Duda, P., Dudek, M. W., Dufour, L., Duk, V., Durante, P., Duras, M. M., Durham, J. M., Durmus, O. D., Dziurda, A., Dzyuba, A., Easo, S., Eckstein, E., Egede, U., Egorychev, A., Egorychev, V., Eisenhardt, S., Ejopu, E., Eklund, L., Elashri, M., Ellbracht, J., Ely, S., Ene, A., Eschle, J., Esen, S., Evans, T., Fabiano, F., Falcao, L. N., Fan, Y., Fang, B., Fantini, L., Faria, M., Farmer, K., Fazzini, D., Felkowski, L., Feng, M., Feo, M., Casani, A. Fernandez, Gomez, M. Fernandez, Fernez, A. D., Ferrari, F., Rodrigues, F. Ferreira, Ferrillo, M., Ferro-Luzzi, M., Filippov, S., Fini, R. A., Fiorini, M., Firlej, M., Fischer, K. L., Fitzgerald, D. S., Fitzpatrick, C., Fiutowski, T., Fleuret, F., Fontana, M., Foreman, L. F., Forty, R., Foulds-Holt, D., Lima, V. Franco, Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Frei, C., Friday, D. A., Fu, J., Führing, Q., Fujii, Y., Fulghesu, T., Gabriel, E., Galati, G., Galati, M. D., Torreira, A. Gallas, Galli, D., Gambetta, S., Gandelman, M., Gandini, P., Ganie, B., Gao, H., Gao, R., Gao, T. Q., Gao, Y., Martin, L. M. Garcia, Moreno, P. Garcia, Pardiñas, J. García, Gardner, P., Garg, K. G., Garrido, L., Gaspar, C., Geertsema, R. E., Gerken, L. L., Gersabeck, E., Gersabeck, M., Gershon, T., Ghizzo, S., Ghorbanimoghaddam, Z., Giambastiani, L., Giasemis, F. I., Gibson, V., Giemza, H. K., Gilman, A. L., Giovannetti, M., Gioventù, A., Girardey, L., Gironell, P. Gironella, Giugliano, C., Giza, M. A., Gkougkousis, E. L., Glaser, F. C., Gligorov, V. V., Göbel, C., Golobardes, E., Golubkov, D., Golutvin, A., Fernandez, S. Gomez, Gomulka, W., Abrantes, F. Goncalves, Goncerz, M., Gong, G., Gooding, J. A., Gorelov, I. V., Gotti, C., Grabowski, J. P., Cardoso, L. A. Granado, Graugés, E., Graverini, E., Grazette, L., Graziani, G., Grecu, A. T., Greeven, L. M., Grieser, N. A., Grillo, L., Gromov, S., Gu, C., Guarise, M., Guerry, L., Guittiere, M., Guliaeva, V., Günther, P. A., Guseinov, A. -K., Gushchin, E., Guz, Y., Gys, T., Habermann, K., Hadavizadeh, T., Hadjivasiliou, C., Haefeli, G., Haen, C., Hajheidari, M., Hallett, G., Halvorsen, M. M., Hamilton, P. M., Hammerich, J., Han, Q., Han, X., Hansmann-Menzemer, S., Hao, L., Harnew, N., Harris, T. H., Hartmann, M., Hashmi, S., He, J., Hemmer, F., Henderson, C., Henderson, R. D. L., Hennequin, A. M., Hennessy, K., Henry, L., Herd, J., Gascon, P. Herrero, Heuel, J., Hicheur, A., Mendizabal, G. Hijano, Horswill, J., Hou, R., Hou, Y., Howarth, N., Hu, J., Hu, W., Hu, X., Huang, W., Hulsbergen, W., Hunter, R. J., Hushchyn, M., Hutchcroft, D., Idzik, M., Ilin, D., Ilten, P., Inglessi, A., Iniukhin, A., Ishteev, A., Ivshin, K., Jacobsson, R., Jage, H., Elles, S. J. Jaimes, Jakobsen, S., Jans, E., Jashal, B. K., Jawahery, A., Jevtic, V., Jiang, E., Jiang, X., Jiang, Y., Jiang, Y. J., John, M., Rajan, A. John Rubesh, Johnson, D., Jones, C. R., Jones, T. P., Joshi, S., Jost, B., Castella, J. Juan, Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kane, M., Kang, Y., Kar, C., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., Kazanecki, M. K., Keizer, F., Kenzie, M., Ketel, T., Khanji, B., Kharisova, A., Kholodenko, S., Khreich, G., Kirn, T., Kirsebom, V. S., Kitouni, O., Klaver, S., Kleijne, N., Klimaszewski, K., Kmiec, M. R., Koliiev, S., Kolk, L., Konoplyannikov, A., Kopciewicz, P., Koppenburg, P., Korolev, M., Kostiuk, I., Kot, O., Kotriakhova, S., Kozachuk, A., Kravchenko, P., Kravchuk, L., Kreps, M., Krokovny, P., Krupa, W., Krzemien, W., Kshyvanskyi, O., Kubis, S., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Gonzalez, P. Laguarta, Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Lanfranchi, G., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. 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Subjects
High Energy Physics - Experiment
Abstract

An amplitude analysis of the $D_{s1}(2460)^+\to D_{s}^{+}\pi^{+}\pi^{-}$ transition is performed simultaneously in $B^{0}\to D^{-}D_{s}^{+}\pi^{+}\pi^{-}$, $B^{+}\to{\bar{D}}^{0} D_{s}^{+}\pi^{+}\pi^{-}$, and $B^{0}\to D^{*-}D_{s}^{+}\pi^{+}\pi^{-}$ decays. The study is based on a data sample of proton-proton collisions recorded with the LHCb detector at centre-of-mass energies of $\sqrt{s}=7,8,$ and $13\,$TeV, corresponding to a total integrated luminosity of $9\,\rm{fb}^{-1}$. A clear double-peak structure is observed in the $m(\pi^{+}\pi^{-})$ spectrum of the $D_{s1}(2460)^{+}\to D_{s}^{+}\pi^{+}\pi^{-}$ decay. The data can be described either with a model including $f_0(500)$, $f_0(980)$ and $f_2(1270)$ resonances, in which the contributions of $f_0(980)$ and $f_2(1270)$ are unexpectedly large, or with a model including $f_0(500)$, a doubly charged open-charm tetraquark state $T_{c\bar{s}}^{++}$ and its isospin partner $T_{c\bar{s}}^{0}$. If the former is considered implausible, the $T_{c\bar{s}}$ states are observed with high significance, and the data are consistent with isospin symmetry. When imposing isospin constraints between the two $T_{c\bar{s}}$ states, their mass and width are determined to be $2327\pm13\pm13\,$MeV and $96\pm16\,^{+170}_{-23}\,$MeV, respectively, where the first uncertainty is statistical and the second is systematic. The mass is slightly below the $DK$ threshold, and a spin-parity of $0^+$ is favoured with high significance., Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lbfence.cern.ch/alcm/public/analysis/full-details/3280/ (LHCb public pages)

Published
2024

12. Test of lepton flavour universality with $B_s^0 \rightarrow \phi \ell^+\ell^-$ decays

Author

LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Balboni, A., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. A., Belin, S., Bellee, V., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bonacci, R. B., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonaura, A., Buonincontri, L., Burke, A. T., Burr, C., Butter, J. 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Juan, Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kane, M., Kang, Y., Kar, C., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., Kazanecki, M. K., Keizer, F., Kenzie, M., Ketel, T., Khanji, B., Kharisova, A., Kholodenko, S., Khreich, G., Kirn, T., Kirsebom, V. S., Kitouni, O., Klaver, S., Kleijne, N., Klimaszewski, K., Kmiec, M. R., Koliiev, S., Kolk, L., Konoplyannikov, A., Kopciewicz, P., Koppenburg, P., Korolev, M., Kostiuk, I., Kot, O., Kotriakhova, S., Kozachuk, A., Kravchenko, P., Kravchuk, L., Kreps, M., Krokovny, P., Krupa, W., Krzemien, W., Kshyvanskyi, O., Kubis, S., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Gonzalez, P. Laguarta, Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Lanfranchi, G., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. Le, Lee, H., Lefèvre, R., Leflat, A., Legotin, S., Lehuraux, M., Cid, E. 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F., Marchevski, R., Marconi, U., Mariani, E., Mariani, S., Benito, C. Marin, Marks, J., Marshall, A. M., Martel, L., Martelli, G., Martellotti, G., Martinazzoli, L., Martinelli, M., Gomez, D. Martinez, Santos, D. Martinez, Vidal, F. Martinez, Granollers, A. Martorell i, Massafferri, A., Matev, R., Mathad, A., Matiunin, V., Matteuzzi, C., Mattioli, K. R., Mauri, A., Maurice, E., Mauricio, J., Mayencourt, P., de Cos, J. Mazorra, Mazurek, M., McCann, M., Mcconnell, L., McGrath, T. H., McHugh, N. T., McNab, A., McNulty, R., Meadows, B., Meier, G., Melnychuk, D., Meng, F. M., Merk, M., Merli, A., Garcia, L. Meyer, Miao, D., Miao, H., Mikhasenko, M., Milanes, D. A., Minotti, A., Minucci, E., Miralles, T., Mitreska, B., Mitzel, D. S., Modak, A., Mohammed, R. A., Moise, R. D., Mokhnenko, S., Cardenas, E. F. Molina, Mombächer, T., Monk, M., Monteil, S., Gomez, A. Morcillo, Morello, G., Morello, M. J., Morgenthaler, M. P., Moron, J., Morren, W., Morris, A. B., Morris, A. G., Mountain, R., Mu, H., Mu, Z. M., Muhammad, E., Muheim, F., Mulder, M., Müller, K., Muñoz-Rojas, F., Murta, R., Naik, P., Nakada, T., Nandakumar, R., Nanut, T., Nasteva, I., Needham, M., Neri, N., Neubert, S., Neufeld, N., Neustroev, P., Nicolini, J., Nicotra, D., Niel, E. M., Nikitin, N., Nogarolli, P., Nogga, P., Normand, C., Fernandez, J. Novoa, Nowak, G., Nunez, C., Nur, H. N., Oblakowska-Mucha, A., Obraztsov, V., Oeser, T., Okamura, S., Okhotnikov, A., Okhrimenko, O., Oldeman, R., Oliva, F., Olocco, M., Onderwater, C. J. G., O'Neil, R. H., Osthues, D., Goicochea, J. M. Otalora, Owen, P., Oyanguren, A., Ozcelik, O., Paciolla, F., Padee, A., Padeken, K. O., Pagare, B., Pais, P. R., Pajero, T., Palano, A., Palutan, M., Pan, X., Panshin, G., Paolucci, L., Papanestis, A., Pappagallo, M., Pappalardo, L. L., Pappenheimer, C., Parkes, C., Passalacqua, B., Passaleva, G., Passaro, D., Pastore, A., Patel, M., Patoc, J., Patrignani, C., Paul, A., Pawley, C. J., Pellegrino, A., Peng, J., Altarelli, M. Pepe, Perazzini, S., Pereima, D., Da Costa, H. Pereira, Castro, A. Pereiro, Perret, P., Perrevoort, A., Perro, A., Petridis, K., Petrolini, A., Pfaller, J. P., Pham, H., Pica, L., Piccini, M., Piccolo, L., Pietrzyk, B., Pietrzyk, G., Pinci, D., Pisani, F., Pizzichemi, M., Placinta, V., Casasus, M. Plo, Poeschl, T., Polci, F., Lener, M. Poli, Poluektov, A., Polukhina, N., Polyakov, I., Polycarpo, E., Ponce, S., Popov, D., Poslavskii, S., Prasanth, K., Prouve, C., Provenzano, D., Pugatch, V., Punzi, G., Qasim, S., Qian, Q. Q., Qian, W., Qin, N., Qu, S., Quagliani, R., Trejo, R. I. Rabadan, Rademacker, J. H., Rama, M., García, M. Ramírez, De Oliveira, V. Ramos, Pernas, M. Ramos, Rangel, M. S., Ratnikov, F., Raven, G., De Miguel, M. Rebollo, Redi, F., Reich, J., Reiss, F., Ren, Z., Resmi, P. K., Ribatti, R., Ricart, G. R., Riccardi, D., Ricciardi, S., Richardson, K., Richardson-Slipper, M., Rinnert, K., Robbe, P., Robertson, G., Rodrigues, E., Alvarez, A. Rodriguez, Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Rodriguez, E. Rodriguez, Roensch, J., Rogachev, A., Rogovskiy, A., Rolf, D. L., Roloff, P., Romanovskiy, V., Vidal, A. Romero, Romolini, G., Ronchetti, F., Rong, T., Rotondo, M., Roy, S. R., Rudolph, M. S., Diaz, M. Ruiz, Fernandez, R. A. Ruiz, Vidal, J. Ruiz, Ryzhikov, A., Ryzka, J., Saavedra-Arias, J. J., Silva, J. J. Saborido, Sadek, R., Sagidova, N., Sahoo, D., Sahoo, N., Saitta, B., Salomoni, M., Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santoro, L., Santovetti, E., Saputi, A., Saranin, D., Sarnatskiy, A., Sarpis, G., Sarpis, M., Satriano, C., Satta, A., Saur, M., Savrina, D., Sazak, H., Sborzacchi, F., Smead, L. G. Scantlebury, Scarabotto, A., Schael, S., Scherl, S., Schiller, M., Schindler, H., Schmelling, M., Schmidt, B., Schmitt, S., Schmitz, H., Schneider, O., Schopper, A., Schulte, N., Schulte, S., Schune, M. H., Schwemmer, R., Schwering, G., Sciascia, B., Sciuccati, A., Sellam, S., Semennikov, A., Senger, T., Soares, M. Senghi, Sergi, A., Serra, N., Sestini, L., Seuthe, A., Shang, Y., Shangase, D. M., Shapkin, M., Sharma, R. S., Shchemerov, I., Shchutska, L., Shears, T., Shekhtman, L., Shen, Z., Sheng, S., Shevchenko, V., Shi, B., Shi, Q., Shimizu, Y., Shmanin, E., Shorkin, R., Shupperd, J. D., Coutinho, R. Silva, Simi, G., Simone, S., Skidmore, N., Skwarnicki, T., Slater, M. W., Smallwood, J. C., Smith, E., Smith, K., Smith, M., Snoch, A., Lavra, L. Soares, Sokoloff, M. D., Soler, F. J. P., Solomin, A., Solovev, A., Solovyev, I., Sommerfeld, N. S., Song, R., Song, Y., Song, Y. S., De Almeida, F. L. Souza, De Paula, B. Souza, Norella, E. Spadaro, Spedicato, E., Speer, J. G., Spiridenkov, E., Spradlin, P., Sriskaran, V., Stagni, F., Stahl, M., Stahl, S., Stanislaus, S., Stein, E. N., Steinkamp, O., Stenyakin, O., Stevens, H., Strekalina, D., Su, Y., Suljik, F., Sun, J., Sun, L., Sundfeld, D., Sutcliffe, W., Swallow, P. N., Swientek, K., Swystun, F., Szabelski, A., Szumlak, T., Tan, Y., Tang, Y., Tat, M. D., Terentev, A., Terzuoli, F., Teubert, F., Thomas, E., Thompson, D. J. D., Tilquin, H., Tisserand, V., T'Jampens, S., Tobin, M., Tomassetti, L., Tonani, G., Tong, X., Machado, D. Torres, Toscano, L., Tou, D. Y., Trippl, C., Tuci, G., Tuning, N., Uecker, L. H., Ukleja, A., Unverzagt, D. J., Urbach, B., Ursov, E., Usachov, A., Ustyuzhanin, A., Uwer, U., Vagnoni, V., Cadenas, V. Valcarce, Valenti, G., Canudas, N. Valls, Van Hecke, H., van Herwijnen, E., Van Hulse, C. B., Van Laak, R., van Veghel, M., Vasquez, G., Gomez, R. Vazquez, Regueiro, P. Vazquez, Sierra, C. Vázquez, Vecchi, S., Velthuis, J. J., Veltri, M., Venkateswaran, A., Verdoglia, M., Vesterinen, M., Benet, D. Vico, Villalba, P. Vidrier, Diaz, M. Vieites, Vilasis-Cardona, X., Figueras, E. Vilella, Villa, A., Vincent, P., Volle, F. C., Bruch, D. vom, Voropaev, N., Vos, K., Vouters, G., Vrahas, C., Wagner, J., Walsh, J., Walton, E. J., Wan, G., Wang, C., Wang, G., Wang, J., Wang, M., Wang, N. W., Wang, R., Wang, X., Wang, X. W., Wang, Y., Wang, Z., Ward, J. A., Waterlaat, M., Watson, N. K., Websdale, D., Wei, Y., Wendel, J., Westhenry, B. D. C., White, C., Whitehead, M., Whiter, E., Wiederhold, A. R., Wiedner, D., Wilkinson, G., Wilkinson, M. K., Williams, M., Williams, M. J., Williams, M. R. J., Williams, R., Williams, Z., Wilson, F. F., Winn, M., Wislicki, W., Witek, M., Witola, L., Wormser, G., Wotton, S. A., Wu, H., Wu, J., Wu, X., Wu, Y., Wu, Z., Wyllie, K., Xian, S., Xiang, Z., Xie, Y., Xu, A., Xu, J., Xu, L., Xu, M., Xu, Z., Yang, D., Yang, K., Yang, S., Yang, X., Yang, Y., Yang, Z., Yeroshenko, V., Yeung, H., Yin, H., Yin, X., Yu, C. Y., Yu, J., Yuan, X., Yuan, Y, Zaffaroni, E., Zavertyaev, M., Zdybal, M., Zenesini, F., Zeng, C., Zeng, M., Zhang, C., Zhang, D., Zhang, J., Zhang, L., Zhang, S., Zhang, Y., Zhang, Y. Z., Zhao, Y., Zharkova, A., Zhelezov, A., Zheng, S. Z., Zheng, X. Z., Zheng, Y., Zhou, T., Zhou, X., Zhou, Y., Zhovkovska, V., Zhu, L. Z., Zhu, X., Zhukov, V., Zhuo, J., Zou, Q., Zuliani, D., and Zunica, G.

Subjects
High Energy Physics - Experiment
Abstract

Lepton flavour universality in rare $b\rightarrow s$ transitions is tested for the first time using $B_s^0$ meson decays. The measurements are performed using $pp$ collision data collected by the LHCb experiment between 2011 and 2018, corresponding to a total integrated luminosity of 9$\,{\rm fb}^{-1}$. Branching fraction ratios between the $B_s^0 \rightarrow \phi e^+e^-$ and $B_s^0 \rightarrow \phi \mu^+\mu^-$ decays are measured in three regions of dilepton mass squared, $q^2$, with $0.1 < q^2 < 1.1$, $1.1 < q^2 < 6.0$, and $15 < q^2 < 19\,{\rm GeV}^2/c^4$. The results agree with the Standard Model expectation of lepton flavour universality., Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lbfence.cern.ch/alcm/public/analysis/full-details/3513/ (LHCb public pages)

Published
2024

13. STLCutters.jl: A scalable geometrical framework library for unfitted finite element discretisations

Author

Martorell, Pere A. and Badia, Santiago

Subjects
Mathematics - Numerical Analysis
Abstract

Approximating partial differential equations for extensive industrial and scientific applications requires leveraging the power of modern high-performance computing. In large-scale parallel computations, the geometrical discretisation rapidly becomes a bottleneck in the simulation pipeline. Unstructured mesh generation is hardly automatic, and meshing algorithms cannot efficiently exploit distributed-memory computers. Adaptive Cartesian meshes are far more advantageous, providing cheap and scalable mesh generation, partitioning, and balancing compared to unstructured meshes. However, Cartesian meshes are not suitable for complex geometries when using standard discretisation techniques. Unfitted finite element methods are a promising solution to the abovementioned problems. Nevertheless, their application is usually constrained to implicit (level-set) geometrical representations. The extension to general geometries, e.g., provided by an STL surface mesh, requires advanced intersection algorithms. This work presents an efficient parallel implementation of all the geometric tools required, e.g., for unfitted finite element methods (in a broad sense), for explicit boundary representations. Such geometries can readily be generated using standard computer-aided design tools. The proposed geometrical workflow utilise a multilevel approach to overlapping computations, effectively eliminating bottlenecks in large-scale computations. The numerical results demonstrate perfect weak scalability over 13,000 processors and one billion cells. All these algorithms are implemented in the open-sopurce STLCutters.jl library, written in the Julia programming language. The library is designed to be used in conjunction with the Gridap.jl library provides a high-level interface to the finite element method.

Published
2024

14. [Translated article] Risk of a Second Skin Cancer in a Cohort of Patients With Nonmelanoma Skin Cancer – Basal Cell Carcinoma or Squamous Cell Carcinoma – Treated With Mohs Micrographic Surgery: A National Prospective Cohort Study

Author

R. Miñano Medrano, J.L. López Estebaranz, O. Sanmartin-Jiménez, J.R. Garcés, M.A. Rodríguez-Prieto, E. Vilarrasa-Rull, E. de Eusebio-Murillo, B. Escutia-Muñoz, Á. Flórez-Menéndez, J.L. Artola-Igarza, A. Alfaro-Rubio, P. Redondo, Y. Delgado-Jiménez, J.M. Sánchez-Schmidt, I. Allende-Markixana, M.L. Alonso-Pacheco, B. García-Bracamonte, P. de la Cueva-Dobao, R. Navarro-Tejedor, C. Ciudad-Blanco, L. Carnero-González, H. Vázquez-Veiga, N. Cano-Martínez, V. Ruiz-Salas, P. Sánchez-Sambucety, R. Botella-Estrada, B. González-Sixto, A. Martorell-Calatayud, P. Gil, V. Morales-Gordillo, A. Toll-Abelló, I. Ocerin-Guerra, M. Mayor-Arenal, R. Suárez-Fernández, L. Sainz-Gaspar, M.A. Descalzo, and I. García-Doval

Subjects
Cirugía micrográfica de Mohs, Carcinoma basocelular, Carcinoma epidermoide cutáneo, Segunda neoplasia, Incidencia, Factores de riesgo, Dermatology, RL1-803, Internal medicine, RC31-1245
Abstract

Objective: Patients with nonmelanoma skin cancer (NMSC)—ie, basal cell carcinoma (BCC) or squamous cell carcinoma (SCC)—have an increased risk of developing a second skin cancer. The aim of this study was to describe the frequency, incidence per 1000 person-years, and predictors of a second skin cancer in a cohort of patients with NMSC treated with Mohs micrographic surgery (MMS). Material and methods: Prospective study of a national cohort of patients with NMSC who underwent MMS at 22 Spanish hospitals between July 2013 and February 2020; case data were recorded in the REGESMOHS registry. The study variables included demographic characteristics, frequency and incidence per 1000 person-years of second skin cancers diagnosed during the study period, and risk factors identified using mixed-effects logistic regression. Results: We analyzed data for 4768 patients who underwent MMS; 4397 (92%) had BCC and 371 (8%) had SCC. Mean follow-up was 2.4 years. Overall, 1201 patients (25%) developed a second skin cancer during follow-up; 1013 of the tumors were BCCs (21%), 154 were SCCs (3%), and 20 were melanomas (0.4%). The incidence was 107 per 1000 person-years (95% CI, 101–113) for any cancer, 90 per 1000 person-years (95% CI, 85–96) for BCC, 14 (95% CI, 12–16) per 1000 person-years for SCC, and 2 (95% CI, 1–3) per 1000 person-years for melanoma. More men than women developed a subsequent skin cancer (738 [61%] vs 463 [39%]). The main risk factors were a history of multiple tumors before diagnosis (relative risk [RR], 4.6; 95% CI, 2.9–7.1), immunosuppression (RR, 2.1; 95% CI, 1.4–3.1), and male sex (RR, 1.6; 95% CI, 1.4–1.9). Conclusion: Patients have an increased risk of developing a second tumor after MMS treatment of NMSC. Risk factors are a history of multiple tumors at diagnosis, immunosuppression, and male sex. Resumen: Objetivo: Los pacientes diagnosticados de cáncer queratinocítico (carcinoma basocelular y carcinoma epidermoide cutáneo) o cáncer cutáneo no melanoma (CCNM) tienen un riesgo aumentado de desarrollar una segunda neoplasia cutánea. Nuestro objetivo es describir la frecuencia, la tasa de incidencia y los factores de riesgo predisponentes para desarrollar una segunda neoplasia cutánea en una cohorte de pacientes tratados mediante cirugía micrográfica de Mohs (CMM). Material y métodos: Estudio prospectivo de una cohorte nacional de pacientes incluidos para realización de CMM para tratar CCNM en 22 centros españoles (julio 2013-febrero 2020) REGESMOHS. Las variables analizadas incluyen las características demográficas, la frecuencia de aparición de segundas neoplasias cutáneas, sus tasas de incidencia y los factores de riesgo, y se estimaron utilizando un modelo de regresión logístico multivariante de efectos mixtos. Resultados: Fueron intervenidos 4.768 pacientes: 4.397 (92%) carcinomas basocelulares y 371 (8%) carcinomas epidermoides. El tiempo medio de seguimiento fue de 2,4 años. Se diagnosticó un nuevo tumor durante el seguimiento en 1.201 pacientes (25%); 1.013 (21%) fueron carcinomas basocelulares, 154 (3%) carcinomas epidermoides cutáneos, 20 melanomas (0,4%) La tasa de incidencia fue de 107 (101-113) por 1.000 personas/año para cualquier tumor; 90 (85-96) para el carcinoma basocelular, 14 (12-16) para el carcinoma epidermoide cutáneo y 2 (1-3) para el melanoma. El riesgo de nueva neoplasia fue mayor en varones que en mujeres 738 (61%) vs. 463 (39%). Los factores de riesgo más significativos fueron la historia de múltiples tumores previos al diagnóstico (RR: 4,6; IC 95%: 2,9-7,1); la inmunosupresión (RR: 2,1; IC 95%: 1,4-3,1) y paciente varón (RR: 1,6; IC 95%: 1,4-1,9). Conclusión: Los pacientes diagnosticados de cáncer queratinocítico intervenido mediante cirugía de Mohs tienen un riesgo aumentado de aparición de segundas neoplasias, sobre todo en aquellos pacientes con historia de tumores múltiples al diagnóstico, inmunodeprimidos y varones.

Published
2022
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15. [Translated article] Artificial intelligence in dermatology: A threat or an opportunity?

Author

A. Martorell, A. Martin-Gorgojo, E. Ríos-Viñuela, J.M. Rueda-Carnero, F. Alfageme, and R. Taberner

Subjects
Inteligencia artificial, Salud, Oncología, Estética, Inflamación, Dermatopatología, Dermatology, RL1-803, Internal medicine, RC31-1245
Abstract

The worldwide explosion of interest in artificial intelligence (AI) has created a before-and-after moment in our lives by generating great improvements in such sectors as the automotive and food production industries. AI has even been called the fourth industrial revolution. Machine learning through AI is helping to improve professional processes and promises to transform the health care sector as we know it in various ways: 1) through applications able to promote health in the general population by providing high-quality information and offering advice for different segments of the population based on prediction models; 2) by developing prediction models based on anonymized clinical data, for preventive purposes in primary care; 3) by analyzing images to provide additional decision-making support for health care providers, for improving specialist care at the secondary level; and 4) through robotics applied to processes that promote health and well-being. However, the medical profession harbors doubts about whether this revolution is a threat or an opportunity owing to a lack of understanding of AI technology and the methods used to validate its applications. This article outlines basic aspects of AI as it is applied in dermatology and reviews the main advances achieved in the last 5 years. Resumen: La irrupción de la inteligencia artificial (IA) a nivel mundial ha supuesto un antes y un después en nuestras vidas, generando grandes mejoras en diferentes sectores, como el de la automoción y el agroalimentario, entre otros, lo que ha llevado a denominarla la cuarta revolución industrial. La AI, capaz de aprender de forma automatizada y de ayudar al profesional a mejorar sus procesos, promete cambiar el ámbito sanitario tal y como lo conocemos mediante: 1) aplicaciones capaces de generar salud en la población general a partir del uso de información de calidad y de segmentación de consejos basados en modelos de predicción; 2) modelos capaces de generar algoritmos de predicción a partir de datos anonimizados procedentes de información clínica, a fin de mejorar la prevención primaria; 3) sistemas de análisis de imagen capaces de dar a los profesionales de la salud un soporte extra en la toma de decisiones, mejorando la prevención secundaria; y 4) aplicación de robótica combinada en la mejora de procesos ligados al ámbito de salud y bienestar.Sin embargo, la falta de conocimiento tanto en este tipo de tecnología, como en los términos y la metodología de validación de la misma, hace que la clase médica dude en si esta revolución supone una amenaza o una oportunidad para la profesión. En el presente artículo de revisión pretendemos introducir una serie de aspectos básicos de la IA aplicada a la dermatología, así como los principales avances sucedidos en este campo en los últimos 5 años.

Published
2022
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16. A Mess of Memory System Benchmarking, Simulation and Application Profiling

Author

Esmaili-Dokht, Pouya, Sgherzi, Francesco, Girelli, Valeria Soldera, Boixaderas, Isaac, Carmin, Mariana, Monemi, Alireza, Armejach, Adria, Mercadal, Estanislao, Llort, German, Radojkovic, Petar, Moreto, Miquel, Gimenez, Judit, Martorell, Xavier, Ayguade, Eduard, Labarta, Jesus, Confalonieri, Emanuele, Dubey, Rishabh, and Adlard, Jason

Subjects
Computer Science - Hardware Architecture
Abstract

The Memory stress (Mess) framework provides a unified view of the memory system benchmarking, simulation and application profiling. The Mess benchmark provides a holistic and detailed memory system characterization. It is based on hundreds of measurements that are represented as a family of bandwidth--latency curves. The benchmark increases the coverage of all the previous tools and leads to new findings in the behavior of the actual and simulated memory systems. We deploy the Mess benchmark to characterize Intel, AMD, IBM, Fujitsu, Amazon and NVIDIA servers with DDR4, DDR5, HBM2 and HBM2E memory. The Mess memory simulator uses bandwidth--latency concept for the memory performance simulation. We integrate Mess with widely-used CPUs simulators enabling modeling of all high-end memory technologies. The Mess simulator is fast, easy to integrate and it closely matches the actual system performance. By design, it enables a quick adoption of new memory technologies in hardware simulators. Finally, the Mess application profiling positions the application in the bandwidth--latency space of the target memory system. This information can be correlated with other application runtime activities and the source code, leading to a better overall understanding of the application's behavior. The current Mess benchmark release covers all major CPU and GPU ISAs, x86, ARM, Power, RISC-V, and NVIDIA's PTX. We also release as open source the ZSim, gem5 and OpenPiton Metro-MPI integrated with the Mess simulator for DDR4, DDR5, Optane, HBM2, HBM2E and CXL memory expanders. The Mess application profiling is already integrated into a suite of production HPC performance analysis tools., Comment: 17 pages; accepted in MICRO-57 (2024), Best paper candidate

Published
2024

17. Applying machine learning to Galactic Archaeology: how well can we recover the origin of stars in Milky Way-like galaxies?

Author

Sante, Andrea, Font, Andreea S., Ortega-Martorell, Sandra, Olier, Ivan, and McCarthy, Ian G.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present several machine learning (ML) models developed to efficiently separate stars formed in-situ in Milky Way-type galaxies from those that were formed externally and later accreted. These models, which include examples from artificial neural networks, decision trees and dimensionality reduction techniques, are trained on a sample of disc-like, Milky Way-mass galaxies drawn from the ARTEMIS cosmological hydrodynamical zoom-in simulations. We find that the input parameters which provide an optimal performance for these models consist of a combination of stellar positions, kinematics, chemical abundances ([Fe/H] and [$\alpha$/Fe]) and photometric properties. Models from all categories perform similarly well, with area under the precision-recall curve (PR-AUC) scores of $\simeq 0.6$. Beyond a galactocentric radius of $5$~kpc, models retrieve $>90\%$ of accreted stars, with a sample purity close to $60\%$, however the purity can be increased by adjusting the classification threshold. For one model, we also include host galaxy-specific properties in the training, to account for the variability of accretion histories of the hosts, however this does not lead to an improvement in performance. The ML models can identify accreted stars even in regions heavily dominated by the in-situ component (e.g., in the disc), and perform well on an unseen suite of simulations (the Auriga simulations). The general applicability bodes well for application of such methods on observational data to identify accreted substructures in the Milky Way without the need to resort to selection cuts for minimising the contamination from in-situ stars.

Published
2024
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18. A real‑world study of clinical characteristics, treatment sequence and outcomes of patients with non-small cell lung cancer and EGFR exon 20 insertion mutations

Author

Suay, Guillermo, Martín-Martorell, Paloma, Aparisi, Francisco, Arnal, María, Guirado, María, Azkárate, Aitor, Garde-Noguera, Javier, Cumplido-Burón, José David, Insa, Amelia, González-Muñoz, José Francisco, Palanca, Sarai, Díaz, María, Sánchez-Hernández, Alfredo, and Juan-Vidal, Óscar

Published
2024
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20. Frequency-dependent covariance reveals critical spatio-temporal patterns of synchronized activity in the human brain

Author

Calvo, Rubén, Martorell, Carles, Morales, Guillermo B., Di Santo, Serena, and Muñoz, Miguel A.

Subjects
Quantitative Biology - Neurons and Cognition, Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Statistical Mechanics, Physics - Biological Physics
Abstract

Recent analyses combining advanced theoretical techniques and high-quality data from thousands of simultaneously recorded neurons provide strong support for the hypothesis that neural dynamics operate near the edge of instability across regions in the brain. However, these analyses, as well as related studies, often fail to capture the intricate temporal structure of brain activity as they primarily rely on time-integrated measurements across neurons. In this study, we present a novel framework designed to explore signatures of criticality across diverse frequency bands and construct a much more comprehensive description of brain activity. Additionally, we introduce a method for projecting brain activity onto a basis of spatio-temporal patterns, facilitating time-dependent dimensionality reduction. Applying this framework to a magnetoencephalography dataset, we observe significant differences in both criticality signatures and spatio-temporal activity patterns between healthy subjects and individuals with Parkinson's disease.

Published
2024

21. Makinote: An FPGA-Based HW/SW Platform for Pre-Silicon Emulation of RISC-V Designs

Author

Perdomo, Elias, Kropotov, Alexander, Cano, Francelly, Zafar, Syed, Cervero, Teresa, Martorell, Xavier, and Salami, Behzad

Subjects
Computer Science - Hardware Architecture, Computer Science - Performance
Abstract

Emulating chip functionality before silicon production is crucial, especially with the increasing prevalence of RISC-V-based designs. FPGAs are promising candidates for such purposes due to their high-speed and reconfigurable architecture. In this paper, we introduce our Makinote, an FPGA-based Cluster platform, hosted at Barcelona Supercomputing Center (BSC-CNS), which is composed of a large number of FPGAs (in total 96 AMD/Xilinx Alveo U55c) to emulate massive size RTL designs (up to 750M ASIC cells). In addition, we introduce our FPGA shell as a powerful tool to facilitate the utilization of such a large FPGA cluster with minimal effort needed by the designers. The proposed FPGA shell provides an easy-to-use interface for the RTL developers to rapidly port such design into several FPGAs by automatically connecting to the necessary ports, e.g., PCIe Gen4, DRAM (DDR4 and HBM), ETH10g/100g. Moreover, specific drivers for exploiting RISC-V based architectures are provided within the set of tools associated with the FPGA shell. We release the tool online for further extensions. We validate the efficiency of our hardware platform (i.e., FPGA cluster) and the software tool (i.e., FPGA Shell) by emulating a RISC-V processor and experimenting HPC Challenge application running on 32 FPGAs. Our results demonstrate that the performance improves by 8 times over the single-FPGA case., Comment: 7 pages, 5 figures, presented in Rapid Simulation and Performance Evaluation for Design 2024 (RAPIDO24) and published in ACM Proceedings of Rapid Simulation and Performance Evaluation for Design

Published
2024
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22. Space-time unfitted finite elements on moving explicit geometry representations

Author

Badia, Santiago, Martorell, Pere A., and Verdugo, Francesc

Subjects
Computer Science - Computational Engineering, Finance, and Science, Mathematics - Numerical Analysis
Abstract

This work proposes a novel variational approximation of partial differential equations on moving geometries determined by explicit boundary representations. The benefits of the proposed formulation are the ability to handle large displacements of explicitly represented domain boundaries without generating body-fitted meshes and remeshing techniques. For the space discretization, we use a background mesh and an unfitted method that relies on integration on cut cells only. We perform this intersection by using clipping algorithms. To deal with the mesh movement, we pullback the equations to a reference configuration (the spatial mesh at the initial time slab times the time interval) that is constant in time. This way, the geometrical intersection algorithm is only required in 3D, another key property of the proposed scheme. At the end of the time slab, we compute the deformed mesh, intersect the deformed boundary with the background mesh, and consider an exact transfer operator between meshes to compute jump terms in the time discontinuous Galerkin integration. The transfer is also computed using geometrical intersection algorithms. We demonstrate the applicability of the method to fluid problems around rotating (2D and 3D) geometries described by oriented boundary meshes. We also provide a set of numerical experiments that show the optimal convergence of the method.

Published
2024
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26. Dynamically selected steady states and criticality in non-reciprocal networks

Author

Martorell, Carles, Calvo, Rubén, Annibale, Alessia, and Muñoz, Miguel A.

Subjects
Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Statistical Mechanics
Abstract

Diverse equilibrium systems with heterogeneous interactions lie at the edge of stability. Such marginally stable states are dynamically selected as the most abundant ones or as those with the largest basins of attraction. On the other hand, systems with non-reciprocal (or asymmetric) interactions are inherently out of equilibrium, and exhibit a rich variety of steady states, including fixed points, limit cycles and chaotic trajectories. How are steady states dynamically selected away from equilibrium? We address this question in a simple neural network model, with a tunable level of non-reciprocity. Our study reveals different types of ordered phases and it shows how non-equilibrium steady states are selected in each phase. In the spin-glass region, the system exhibits marginally stable behaviour for reciprocal (or symmetric) interactions and it smoothly transitions to chaotic dynamics, as the non-reciprocity (or asymmetry) in the couplings increases. Such region, on the other hand, shrinks and eventually disappears when couplings become anti-symmetric. Our results are relevant to advance the knowledge of disordered systems beyond the paradigm of reciprocal couplings, and to develop an interface between statistical physics of equilibrium spin-glasses and dynamical systems theory.

Published
2023

27. High order unfitted finite element discretizations for explicit boundary representations

Author

Martorell, Pere A. and Badia, Santiago

Subjects
Computer Science - Computational Engineering, Finance, and Science, Mathematics - Numerical Analysis
Abstract

When modeling scientific and industrial problems, geometries are typically modeled by explicit boundary representations obtained from computer-aided design software. Unfitted (also known as embedded or immersed) finite element methods offer a significant advantage in dealing with complex geometries, eliminating the need for generating unstructured body-fitted meshes. However, current unfitted finite elements on nonlinear geometries are restricted to implicit (possibly high-order) level set geometries. In this work, we introduce a novel automatic computational pipeline to approximate solutions of partial differential equations on domains defined by explicit nonlinear boundary representations. For the geometrical discretization, we propose a novel algorithm to generate quadratures for the bulk and surface integration on nonlinear polytopes required to compute all the terms in unfitted finite element methods. The algorithm relies on a nonlinear triangulation of the boundary, a kd-tree refinement of the surface cells that simplify the nonlinear intersections of surface and background cells to simple cases that are diffeomorphically equivalent to linear intersections, robust polynomial root-finding algorithms and surface parameterization techniques. We prove the correctness of the proposed algorithm. We have successfully applied this algorithm to simulate partial differential equations with unfitted finite elements on nonlinear domains described by computer-aided design models, demonstrating the robustness of the geometric algorithm and showing high-order accuracy of the overall method.

Published
2023
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28. Structural connectivity modifications following deep brain stimulation of the subcallosal cingulate and nucleus accumbens in severe anorexia nervosa

Author

Abellaneda-Pérez, Kilian, Delgado-Martínez, Ignacio, Salgado, Purificación, Ginés, José María, Guardiola, Rocío, Vaqué-Alcázar, Lídia, Roca-Ventura, Alba, Molist-Puigdomènech, Roger, Manero, Rosa María, Viles-Garcia, Marc, Medrano-Martorell, Santiago, Bartrés-Faz, David, Pascual-Leone, Alvaro, Pérez-Solà, Víctor, and Villalba-Martínez, Gloria

Published
2024
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30. Correction: ENDOLUNG trial. A phase 1/2 study of the Akt/mTOR inhibitor and autophagy inducer Ibrilatazar (ABTL0812) in combination with paclitaxel/carboplatin in patients with advanced/recurrent endometrial cancer: Alexandra Leary

Author

Leary, Alexandra, Estévez-García, Purificación, Sabatier, Renaud, Ray-Coquard, Isabelle, Romeo, Margarita, Barretina-Ginesta, Pilar, Gil-Martin, Marta, Garralda, Elena, Bosch-Barrera, Joaquim, Morán, Teresa, Martin-Martorell, Paloma, Nadal, Ernest, Gascón, Pere, Rodon, Jordi, Lizcano, Jose M, Muñoz-Guardiola, Pau, Fierro-Durán, Gemma, Pedrós-Gámez, Oriol, Pérez-Montoyo, Héctor, Yeste-Velasco, Marc, Cortal, Marc, Pérez-Campos, Antonio, Alfon, Jose, Domenech, Carles, Pérez-Fidalgo, Alejandro, and Oaknin, Ana

Published
2024
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31. ENDOLUNG trial. A phase 1/2 study of the Akt/mTOR inhibitor and autophagy inducer Ibrilatazar (ABTL0812) in combination with paclitaxel/carboplatin in patients with advanced/recurrent endometrial cancer

Author

Leary, Alexandra, Estévez-García, Purificación, Sabatier, Renaud, Ray-Coquard, Isabelle, Romeo, Margarita, Barretina-Ginesta, Pilar, Gil-Martin, Marta, Garralda, Elena, Bosch-Barrera, Joaquim, Morán, Teresa, Martin-Martorell, Paloma, Nadal, Ernest, Gascón, Pere, Rodon, Jordi, Lizcano, Jose M, Muñoz-Guardiola, Pau, Fierro-Durán, Gemma, Pedrós-Gámez, Oriol, Pérez-Montoyo, Héctor, Yeste-Velasco, Marc, Cortal, Marc, Pérez-Campos, Antonio, Alfon, Jose, Domenech, Carles, Pérez-Fidalgo, Alejandro, and Oaknin, Ana

Published
2024
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35. Kissing to Find a Match: Efficient Low-Rank Permutation Representation

Author

Dröge, Hannah, Lähner, Zorah, Bahat, Yuval, Martorell, Onofre, Heide, Felix, and Möller, Michael

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

Permutation matrices play a key role in matching and assignment problems across the fields, especially in computer vision and robotics. However, memory for explicitly representing permutation matrices grows quadratically with the size of the problem, prohibiting large problem instances. In this work, we propose to tackle the curse of dimensionality of large permutation matrices by approximating them using low-rank matrix factorization, followed by a nonlinearity. To this end, we rely on the Kissing number theory to infer the minimal rank required for representing a permutation matrix of a given size, which is significantly smaller than the problem size. This leads to a drastic reduction in computation and memory costs, e.g., up to $3$ orders of magnitude less memory for a problem of size $n=20000$, represented using $8.4\times10^5$ elements in two small matrices instead of using a single huge matrix with $4\times 10^8$ elements. The proposed representation allows for accurate representations of large permutation matrices, which in turn enables handling large problems that would have been infeasible otherwise. We demonstrate the applicability and merits of the proposed approach through a series of experiments on a range of problems that involve predicting permutation matrices, from linear and quadratic assignment to shape matching problems., Comment: 13 pages, 6 figures

Published
2023

36. Pandemic-Period Enrollment and Persistence in California Community Colleges

Author

University of California, Davis. Wheelhouse: The Center for Community College Leadership and Research, Robert Linden, Michal Kurlaender, Paco Martorell, and Scott E. Carrell

Abstract

Using rich administrative data from the California Community Colleges Chancellor's Office that tracks each student longitudinally, this analysis examines how the onset of the pandemic affected student enrollment duration. Data are disaggregated by student characteristics and college campuses in order to understand variable impacts and equity implications.

Published
2022

41. Can we screen for heart disease in children at public health centres? A multicentre observational study of screening for heart disease with a risk of sudden death in children

Author

Greciano Calero, Paula, Escribá Bori, Silvia, Costa Orvay, Juan Antonio, González Pons, Nina, Martín Pérez, María del Carmen, Cardona Alfonseca, Dolores, Nogales Velázquez, Cristina, Verd Vallespir, Sergi, Tur Salom, Alicia Esther, Chiandetti, Antonella, Navarro Noguera, Marcos, Grau Blanch, Anna, Rotger Genestar, María Magdalena, Mambié Meléndez, Marianna, Fernández Hidalgo, Mercedes, Seguí Llinas, Juana María, Martorell Bon, Laura, Arestuche Aguilar, Patricia, Garrido Conde, Beatriz, Sánchez Grao, María del Valle, Sarraff Trujillo, Katia, Muntaner Alonso, Antoni, Grimalt Ferragut, Catalina, Soriano Marco, Andrea, Gómez Rojas, Viviana, and Pol Serra, Juan

Published
2024
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43. Disparate Impacts of COVID-19 Disruptions for California College Students

Author

Sherrie Re, Elizabeth Friedmann, Michal Kurlaender, Paco Martorell, Derek Rury, Ryan Fuller, Jessica Moldoff, and Patrick Perry

Abstract

This paper documents the experience of California college students in the midst of the pandemic as their academic and home lives were disrupted. The analysis relies on a survey sent to all financial aid applicants statewide. Survey respondents include nearly 100,000 students enrolled in both two-year and four-year postsecondary institutions. Results reveal multiple stressors strained the educational experience and trajectories of many students. These stressors were not evenly distributed. In particular, students from low-income backgrounds were more likely to face increased financial stress, additional home responsibilities, and difficulty accessing the online learning environment, when compared to their higher-income peers.

Published
2022
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44. 3D printed polymeric stent design: Mechanical testing and computational modeling

Author

Francesc Canalejo-Codina, Mariola Cano-Morenilla, Jordi Martorell, Mercedes Balcells, Marta Pegueroles, and Andrés A. García-Granada

Subjects
Additive manufacturing, Bioresorbable stent, Poly(L-lactide-co-ε-caprolactone), Mechanical performance, Crush resistance, Finite element analysis, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

Polymer-based bioresorbable scaffolds (BRS) aim to reduce the long-term issues associated with metal stents. Yet, first-generation BRS designs experienced a significantly higher rate of clinical failures compared to permanent implants. This prompted the development of alternative scaffolds, such as the poly(L-lactide-co-ε-caprolactone) (PLCL) solvent-casted stent, whose mechanical performance has yet to be addressed. This study examines the mechanical behavior of this novel scaffold across a wide range of parallel and radial compression diameters. The analysis highlights the scaffold’s varying responses under different loading conditions and provides insights into interpreting simulation model parameters to accurately reflect experimental results.Stents demonstrated a parallel crush resistance of 0.11 N/mm at maximum compression, whereas the radial forces were significantly higher, reaching up to 1.80 N/mm. Additionally, the parallel test keeps the stent in the elastic regime, with almost no regions exceeding 50 MPa of stress, while the radial test causes significant structural deformation, with localized plastic strain reaching up to 30 %. Results showed that underestimating yield strain in computational models leads to discrepancies with experimental results, being 5 % the most accurate value for matching computational and experimental results for PLCL solvent-casted stents.This comprehensive approach is vital for optimizing BRS design and predicting clinical performance.

Published
2024
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46. Accelerated Cortical Thinning in Schizophrenia Is Associated With Rare and Common Predisposing Variation to Schizophrenia and Neurodevelopmental Disorders

Author

González-Peñas, Javier, Díaz-Caneja, Covadonga M., Costas, Javier, Gurriarán, Xaquín, Andreu-Bernabeu, Álvaro, Fañanas, Lourdes, Rosa de la Cruz, Araceli, Arias, Bárbara, Bobes, Julio, Pinto, Ana González, Crespo-Facorro, B., Martorell, L., Vilella, Elisabet, Muntané, Gerard, Moltó, María Dolores, Escartí, María José, Rivero, Olga, Parellada, Mara, Moreno, Carmen, Arango, Celso, Alloza, Clara, Brouwer, Rachel, González-Lois, Noemí, Gallego, Ana Guil, de Hoyos, Lucía, Romero-García, Rafael, Fañanás, Lourdes, González-Pinto, Ana, Crespo-Facorro, Benedicto, Martorell, Lourdes, Arrojo, Manuel, Gutiérrez-Zotes, Alfonso, Perez-Rando, Marta, Buimer, Elizabeth, van Haren, Neeltje, Cahn, Wiepke, O’Donovan, Michael, Kahn, René S., Pol, Hilleke Hulshoff, Janssen, Joost, and Schnack, Hugo

Published
2024
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47. The TEXTAROSSA Project: Cool all the Way Down to the Hardware.

Author

Antonio Filgueras, Giovanni Agosta, Marco Aldinucci, Carlos álvarez 0001, Pasqua D'Ambra, Massimo Bernaschi, Andrea Biagioni, Daniele Cattaneo 0002, Alessandro Celestini, Massimo Celino, Carlotta Chiarini, Francesca Lo Cicero, Paolo Cretaro, William Fornaciari, Ottorino Frezza, Andrea Galimberti, Francesco Giacomini, Juan Miguel De Haro Ruiz, Francesco Iannone, Daniel Jaschke, Daniel Jiménez-González, Michal Kulczewski, Alberto Leva, Alessandro Lonardo, Michele Martinelli, Xavier Martorell, Simone Montangero, Lucas Morais, Ariel Oleksiak, Paolo Palazzari, Luca Pontisso, Federico Reghenzani, Cristian Rossi, Sergio Saponara, Carlo Saverio Lodi, Francesco Simula, Federico Terraneo, Piero Vicini, Miquel Vidal, Davide Zoni, and Giuseppe Zummo

Published
2024
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