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1,129 results on '"Trueba, P"'

1. ProveRAG: Provenance-Driven Vulnerability Analysis with Automated Retrieval-Augmented LLMs

Author

Fayyazi, Reza, Trueba, Stella Hoyos, Zuzak, Michael, and Yang, Shanchieh Jay

Subjects
Computer Science - Cryptography and Security, Computer Science - Information Retrieval
Abstract

In cybersecurity, security analysts face the challenge of mitigating newly discovered vulnerabilities in real-time, with over 300,000 Common Vulnerabilities and Exposures (CVEs) identified since 1999. The sheer volume of known vulnerabilities complicates the detection of patterns for unknown threats. While LLMs can assist, they often hallucinate and lack alignment with recent threats. Over 25,000 vulnerabilities have been identified so far in 2024, which are introduced after popular LLMs' (e.g., GPT-4) training data cutoff. This raises a major challenge of leveraging LLMs in cybersecurity, where accuracy and up-to-date information are paramount. In this work, we aim to improve the adaptation of LLMs in vulnerability analysis by mimicking how analysts perform such tasks. We propose ProveRAG, an LLM-powered system designed to assist in rapidly analyzing CVEs with automated retrieval augmentation of web data while self-evaluating its responses with verifiable evidence. ProveRAG incorporates a self-critique mechanism to help alleviate omission and hallucination common in the output of LLMs applied in cybersecurity applications. The system cross-references data from verifiable sources (NVD and CWE), giving analysts confidence in the actionable insights provided. Our results indicate that ProveRAG excels in delivering verifiable evidence to the user with over 99% and 97% accuracy in exploitation and mitigation strategies, respectively. This system outperforms direct prompting and chunking retrieval in vulnerability analysis by overcoming temporal and context-window limitations. ProveRAG guides analysts to secure their systems more effectively while documenting the process for future audits.

Published
2024

2. Lack of wastewater treatment in a small town drives the spread of ESBL-producing Escherichia coli in irrigation waters.

Author

VanderYacht, Thomas, Salinas, Liseth, Remerleitch, Tilden, Walas, Nikolina, Ho, Tin, Trueba, Gabriel, and Graham, Jay P

Subjects
Earth Sciences, Environmental Sciences, Biological Sciences, Agronomy & Agriculture, Biological sciences, Earth sciences, Environmental sciences
Abstract

Antibiotic resistance (ABR) is a critical and growing global challenge, especially in low- and middle-income countries. Ecuador has made great progress in connecting households to piped water supplies; however, the collection and treatment of domestic wastewater has lagged. This infrastructural gap may be accelerating the spread of ABR into surface waters used downstream for irrigation. We studied the contributions of a small town in Ecuador to the prevalence of extended-spectrum β-lactamase-producing Escherichia coli in a glacial stream used for irrigating crops. The study analyzed water samples upstream (n = 60) and downstream (n = 60) of the town of Píntag as well as 30 lettuce samples irrigated by surface waters downstream of the town. A subset of third generation cephalosporin resistant E. coli (3GCR-EC) isolates (n = 58) were sequenced to characterize antibiotic resistance genes and pathogenic lineages. Our results showed that there was nearly a three-log increase in mean E. coli colony forming units in the downstream samples versus upstream. At the upstream sites above the town of Píntag, 6.7% of water samples were positive for 3GCR-EC compared to 100% of samples collected at the downstream sites. Additionally, 70.1% of sequenced 3GCR-EC isolates collected at downstream sites carried blaCTX-M genes and 3.4% belonged to pandemic lineages ST131 and ST10. As countries develop household piped water infrastructure, attention should focus on how the lack of domestic wastewater collection and treatment may accelerate the spread of ABR in waterways and the food system.

Published
2024

3. Detection of mobile colistin resistance genes mcr-9.1 and mcr-10.1 in Enterobacter asburiae from Ecuadorian children.

Author

Cifuentes, Sara, Graham, Jay, Trueba, Gabriel, and Cádenas, Paúl

Subjects
colistin, enterobacter, mcr
Abstract

Colistin is one of the last-line treatments for multi-drug resistant Gram-negative bacterial infections. The emergence of mobile colistin resistance genes has driven global concern and triggered the need for surveillance. Our report reveals the identification of mcr-9.1 and mcr-10.1 in Ecuador by employing a proximity ligation technique.

Published
2024

4. Analysis of Antibiotic Resistance Genes (ARGs) across Diverse Bacterial Species in Shrimp Aquaculture

Author

Mitchell, Tilden M, Ho, Tin, Salinas, Liseth, VanderYacht, Thomas, Walas, Nikolina, Trueba, Gabriel, and Graham, Jay P

Subjects
Medical Microbiology, Biomedical and Clinical Sciences, Biodefense, Emerging Infectious Diseases, Infectious Diseases, Antimicrobial Resistance, Infection, Pharmacology and pharmaceutical sciences
Abstract

There is little information available on antibiotic resistance (ABR) within shrimp aquaculture environments. The aim of this study was to investigate the presence of antibiotic resistance genes (ARGs) in shrimp farming operations in Atacames, Ecuador. Water samples (n = 162) and shrimp samples (n = 54) were collected from three shrimp farming operations. Samples were cultured and a subset of isolates that grew in the presence of ceftriaxone, a third-generation cephalosporin, were analyzed using whole-genome sequencing (WGS). Among the sequenced isolates (n = 44), 73% of the isolates contained at least one ARG and the average number of ARGs per isolate was two, with a median of 3.5 ARGs. Antibiotic resistance genes that confer resistance to the β-lactam class of antibiotics were observed in 65% of the sequenced isolates from water (20/31) and 54% of the isolates from shrimp (7/13). We identified 61 different ARGs across the 44 sequenced isolates, which conferred resistance to nine antibiotic classes. Over half of all sequenced isolates (59%, n = 26) carried ARGs that confer resistance to more than one class of antibiotics. ARGs for certain antibiotic classes were more common, including beta-lactams (26 ARGs); aminoglycosides (11 ARGs); chloramphenicol (three ARGs); and trimethoprim (four ARGs). Sequenced isolates consisted of a diverse array of bacterial orders and species, including Escherichia coli (48%), Klebsiella pneumoniae (7%), Aeromonadales (7%), Pseudomonadales (16%), Enterobacter cloacae (2%), and Citrobacter freundii (2%). Many ARGs were shared across diverse species, underscoring the risk of horizontal gene transfer in these environments. This study indicated the widespread presence of extended-spectrum β-lactamase (ESBL) genes in shrimp aquaculture, including blaCTX-M, blaSHV, and blaTEM genes. Increased antibiotic resistance surveillance of shrimp farms and identification of aquaculture operation-level risk factors, such as antibiotic use, will likely be important for mitigating the spread of ARGs of clinical significance.

Published
2024

5. Enhancing the Stability of LLM-based Speech Generation Systems through Self-Supervised Representations

Author

Martín-Cortinas, Álvaro, Sáez-Trigueros, Daniel, Vallés-Pérez, Iván, Tura-Vecino, Biel, Biliński, Piotr, Lajszczak, Mateusz, Beringer, Grzegorz, Barra-Chicote, Roberto, and Lorenzo-Trueba, Jaime

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Large Language Models (LLMs) are one of the most promising technologies for the next era of speech generation systems, due to their scalability and in-context learning capabilities. Nevertheless, they suffer from multiple stability issues at inference time, such as hallucinations, content skipping or speech repetitions. In this work, we introduce a new self-supervised Voice Conversion (VC) architecture which can be used to learn to encode transitory features, such as content, separately from stationary ones, such as speaker ID or recording conditions, creating speaker-disentangled representations. Using speaker-disentangled codes to train LLMs for text-to-speech (TTS) allows the LLM to generate the content and the style of the speech only from the text, similarly to humans, while the speaker identity is provided by the decoder of the VC model. Results show that LLMs trained over speaker-disentangled self-supervised representations provide an improvement of 4.7pp in speaker similarity over SOTA entangled representations, and a word error rate (WER) 5.4pp lower. Furthermore, they achieve higher naturalness than human recordings of the LibriTTS test-other dataset. Finally, we show that using explicit reference embedding negatively impacts intelligibility (stability), with WER increasing by 14pp compared to the model that only uses text to infer the style., Comment: 10 pages, 1 figure, 3 tables

Published
2024

6. IS26 drives the dissemination of bla CTX-M genes in an Ecuadorian community.

Author

Salinas, Liseth, Cárdenas, Paúl, Trueba, Gabriel, and Graham, Jay

Subjects
Escherichia coli, IS26, antimicrobial resistance, bla CTX-M, horizontal gene transfer
Abstract

The horizontal gene transfer events are the major contributors to the current spread of CTX-M-encoding genes, the most common extended-spectrum β-lactamase (ESBL), and many clinically crucial antimicrobial resistance (AMR) genes. This study presents evidence of the critical role of IS26 transposable element for the mobility of bla CTX-M gene among Escherichia coli isolates from children and domestic animals in the community. We suggest that the nucleotide sequences of IS26-bla CTX-M could be used to study bla CTX-M transmission between humans, domestic animals, and the environment, because understanding of the dissemination patterns of AMR genes is critical to implement effective measures to slow down the dissemination of these clinically important genes.

Published
2024

7. Multilingual context-based pronunciation learning for Text-to-Speech

Author

Comini, Giulia, Ribeiro, Manuel Sam, Yang, Fan, Shim, Heereen, and Lorenzo-Trueba, Jaime

Subjects
Computer Science - Computation and Language, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Phonetic information and linguistic knowledge are an essential component of a Text-to-speech (TTS) front-end. Given a language, a lexicon can be collected offline and Grapheme-to-Phoneme (G2P) relationships are usually modeled in order to predict the pronunciation for out-of-vocabulary (OOV) words. Additionally, post-lexical phonology, often defined in the form of rule-based systems, is used to correct pronunciation within or between words. In this work we showcase a multilingual unified front-end system that addresses any pronunciation related task, typically handled by separate modules. We evaluate the proposed model on G2P conversion and other language-specific challenges, such as homograph and polyphones disambiguation, post-lexical rules and implicit diacritization. We find that the multilingual model is competitive across languages and tasks, however, some trade-offs exists when compared to equivalent monolingual solutions., Comment: 5 pages, 2 figures, 5 tables. Interspeech 2023

Published
2023

8. Comparing normalizing flows and diffusion models for prosody and acoustic modelling in text-to-speech

Author

Zhang, Guangyan, Merritt, Thomas, Ribeiro, Manuel Sam, Tura-Vecino, Biel, Yanagisawa, Kayoko, Pokora, Kamil, Ezzerg, Abdelhamid, Cygert, Sebastian, Abbas, Ammar, Bilinski, Piotr, Barra-Chicote, Roberto, Korzekwa, Daniel, and Lorenzo-Trueba, Jaime

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Neural text-to-speech systems are often optimized on L1/L2 losses, which make strong assumptions about the distributions of the target data space. Aiming to improve those assumptions, Normalizing Flows and Diffusion Probabilistic Models were recently proposed as alternatives. In this paper, we compare traditional L1/L2-based approaches to diffusion and flow-based approaches for the tasks of prosody and mel-spectrogram prediction for text-to-speech synthesis. We use a prosody model to generate log-f0 and duration features, which are used to condition an acoustic model that generates mel-spectrograms. Experimental results demonstrate that the flow-based model achieves the best performance for spectrogram prediction, improving over equivalent diffusion and L1 models. Meanwhile, both diffusion and flow-based prosody predictors result in significant improvements over a typical L2-trained prosody models., Comment: 5 pages, 2 figures, 5 tables. Interspeech 2023

Published
2023

9. Improving grapheme-to-phoneme conversion by learning pronunciations from speech recordings

Author

Ribeiro, Manuel Sam, Comini, Giulia, and Lorenzo-Trueba, Jaime

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Computation and Language
Abstract

The Grapheme-to-Phoneme (G2P) task aims to convert orthographic input into a discrete phonetic representation. G2P conversion is beneficial to various speech processing applications, such as text-to-speech and speech recognition. However, these tend to rely on manually-annotated pronunciation dictionaries, which are often time-consuming and costly to acquire. In this paper, we propose a method to improve the G2P conversion task by learning pronunciation examples from audio recordings. Our approach bootstraps a G2P with a small set of annotated examples. The G2P model is used to train a multilingual phone recognition system, which then decodes speech recordings with a phonetic representation. Given hypothesized phoneme labels, we learn pronunciation dictionaries for out-of-vocabulary words, and we use those to re-train the G2P system. Results indicate that our approach consistently improves the phone error rate of G2P systems across languages and amount of available data., Comment: 5 pages, 2 figures, 4 tables. Interspeech 2023

Published
2023

10. Risk factors for extended-spectrum beta-lactamase (ESBL)-producing E. coli carriage among children in a food animal-producing region of Ecuador: A repeated measures observational study.

Author

Amato, Heather, Loayza, Fernanda, Salinas, Liseth, Paredes, Diana, Garcia, Daniela, Sarzosa, Soledad, Saraiva-Garcia, Carlos, Johnson, Timothy, Riley, Lee, Trueba, Gabriel, Graham, Jay, and Pickering, Amy

Abstract

BACKGROUND: The spread of antibiotic-resistant bacteria may be driven by human-animal-environment interactions, especially in regions with limited restrictions on antibiotic use, widespread food animal production, and free-roaming domestic animals. In this study, we aimed to identify risk factors related to commercial food animal production, small-scale or backyard food animal production, domestic animal ownership, and practices related to animal handling, waste disposal, and antibiotic use in Ecuadorian communities. METHODS AND FINDINGS: We conducted a repeated measures study from 2018 to 2021 in 7 semirural parishes of Quito, Ecuador to identify determinants of third-generation cephalosporin-resistant E. coli (3GCR-EC) and extended-spectrum beta-lactamase E. coli (ESBL-EC) in children. We collected 1,699 fecal samples from 600 children and 1,871 domestic animal fecal samples from 376 of the same households at up to 5 time points per household over the 3-year study period. We used multivariable log-binomial regression models to estimate relative risks (RR) of 3GCR-EC and ESBL-EC carriage, adjusting for child sex and age, caregiver education, household wealth, and recent child antibiotic use. Risk factors for 3GCR-EC included living within 5 km of more than 5 commercial food animal operations (RR: 1.26; 95% confidence interval (CI): 1.10, 1.45; p-value: 0.001), household pig ownership (RR: 1.23; 95% CI: 1.02, 1.48; p-value: 0.030) and child pet contact (RR: 1.23; 95% CI: 1.09, 1.39; p-value: 0.001). Risk factors for ESBL-EC were dog ownership (RR: 1.35; 95% CI: 1.00, 1.83; p-value: 0.053), child pet contact (RR: 1.54; 95% CI: 1.10, 2.16; p-value: 0.012), and placing animal feces on household land/crops (RR: 1.63; 95% CI: 1.09, 2.46; p-value: 0.019). The primary limitations of this study are the use of proxy and self-reported exposure measures and the use of a single beta-lactamase drug (ceftazidime with clavulanic acid) in combination disk diffusion tests for ESBL confirmation, potentially underestimating phenotypic ESBL production among cephalosporin-resistant E. coli isolates. To improve ESBL determination, it is recommended to use 2 combination disk diffusion tests (ceftazidime with clavulanic acid and cefotaxime with clavulanic acid) for ESBL confirmatory testing. Future studies should also characterize transmission pathways by assessing antibiotic resistance in commercial food animals and environmental reservoirs. CONCLUSIONS: In this study, we observed an increase in enteric colonization of antibiotic-resistant bacteria among children with exposures to domestic animals and their waste in the household environment and children living in areas with a higher density of commercial food animal production operations.

Published
2023

11. Leveraging the COVID-19 pandemic as a natural experiment to assess changes in antibiotic use and antibiotic-resistant E. coli carriage in semi-rural Ecuador.

Author

Amato, Heather, Loayza, Fernanda, Salinas, Liseth, Paredes, Diana, García, Daniela, Sarzosa, Soledad, Saraiva-Garcia, Carlos, Johnson, Timothy, Pickering, Amy, Riley, Lee, Trueba, Gabriel, and Graham, Jay

Subjects
Child, Humans, Ecuador, Escherichia coli, Pandemics, Angiotensin Receptor Antagonists, Rural Population, COVID-19, Angiotensin-Converting Enzyme Inhibitors, SARS-CoV-2, Anti-Bacterial Agents
Abstract

The coronavirus 2019 (COVID-19) pandemic has had significant impacts on health systems, population dynamics, public health awareness, and antibiotic stewardship, which could affect antibiotic resistant bacteria (ARB) emergence and transmission. In this study, we aimed to compare knowledge, attitudes, and practices (KAP) of antibiotic use and ARB carriage in Ecuadorian communities before versus after the COVID-19 pandemic began. We leveraged data collected for a repeated measures observational study of third-generation cephalosporin-resistant E. coli (3GCR-EC) carriage among children in semi-rural communities in Quito, Ecuador between July 2018 and September 2021. We included 241 households that participated in surveys and child stool sample collection in 2019, before the pandemic, and in 2021, after the pandemic began. We estimated adjusted Prevalence Ratios (aPR) and 95% Confidence Intervals (CI) using logistic and Poisson regression models. Child antibiotic use in the last 3 months declined from 17% pre-pandemic to 5% in 2021 (aPR: 0.30; 95% CI 0.15, 0.61) and 3GCR-EC carriage among children declined from 40 to 23% (aPR: 0.48; 95% CI 0.32, 0.73). Multi-drug resistance declined from 86 to 70% (aPR: 0.32; 95% CI 0.13; 0.79), the average number of antibiotic resistance genes (ARGs) per 3GCR-EC isolate declined from 9.9 to 7.8 (aPR of 0.79; 95% CI 0.65, 0.96), and the diversity of ARGs was lower in 2021. In the context of Ecuador, where COVID-19 prevention and control measures were strictly enforced after its major cities experienced some of the worlds the highest mortality rates from SARS-CoV-2 infections, antibiotic use and ARB carriage declined in semi-rural communities of Quito from 2019 to 2021.

Published
2023

15. Azimuthal anisotropy of jet particles in p-Pb and Pb-Pb collisions at s NN $$ \sqrt{{\textrm{s}}_{\textrm{NN}}} $$ = 5.02 TeV

Author

The ALICE collaboration, S. Acharya, D. Adamová, A. Adler, G. Aglieri Rinella, M. Agnello, N. Agrawal, Z. Ahammed, S. Ahmad, S. U. Ahn, I. Ahuja, A. Akindinov, M. Al-Turany, D. Aleksandrov, B. Alessandro, H. M. Alfanda, R. Alfaro Molina, B. Ali, A. Alici, N. Alizadehvandchali, A. Alkin, J. Alme, G. Alocco, T. Alt, I. Altsybeev, J. R. Alvarado, M. N. Anaam, C. Andrei, A. Andronic, V. Anguelov, F. Antinori, P. Antonioli, N. Apadula, L. Aphecetche, H. Appelshäuser, C. Arata, S. Arcelli, M. Aresti, R. Arnaldi, J. G. M. C. A. Arneiro, I. C. Arsene, M. Arslandok, A. Augustinus, R. Averbeck, M. D. Azmi, A. Badalà, J. Bae, Y. W. Baek, X. Bai, R. Bailhache, Y. Bailung, A. Balbino, A. Baldisseri, B. Balis, D. Banerjee, Z. Banoo, R. Barbera, F. Barile, L. Barioglio, M. Barlou, G. G. Barnaföldi, L. S. Barnby, V. Barret, L. Barreto, C. Bartels, K. Barth, E. Bartsch, N. Bastid, S. Basu, G. Batigne, D. Battistini, B. Batyunya, D. Bauri, J. L. Bazo Alba, I. G. Bearden, C. Beattie, P. Becht, D. Behera, I. Belikov, A. D. C. Bell Hechavarria, F. Bellini, R. Bellwied, S. Belokurova, V. Belyaev, G. Bencedi, S. Beole, Y. Berdnikov, A. Berdnikova, L. Bergmann, M. G. Besoiu, L. Betev, P. P. Bhaduri, A. Bhasin, M. A. Bhat, B. Bhattacharjee, L. Bianchi, N. Bianchi, J. Bielčík, J. Bielčíková, J. Biernat, A. P. Bigot, A. Bilandzic, G. Biro, S. Biswas, N. Bize, J. T. Blair, D. Blau, M. B. Blidaru, N. Bluhme, C. Blume, G. Boca, F. Bock, T. Bodova, A. Bogdanov, S. Boi, J. Bok, L. Boldizsár, M. Bombara, P. M. Bond, G. Bonomi, H. Borel, A. Borissov, A. G. Borquez Carcamo, H. Bossi, E. Botta, Y. E. M. Bouziani, L. Bratrud, P. Braun-Munzinger, M. Bregant, M. Broz, G. E. Bruno, M. D. Buckland, D. Budnikov, H. Buesching, S. Bufalino, O. Bugnon, P. Buhler, Z. Buthelezi, S. A. Bysiak, M. Cai, H. Caines, A. Caliva, E. Calvo Villar, J. M. M. Camacho, P. Camerini, F. D. M. Canedo, S. L. Cantway, M. Carabas, A. A. Carballo, F. Carnesecchi, R. Caron, L. A. D. Carvalho, J. Castillo Castellanos, F. Catalano, C. Ceballos Sanchez, I. Chakaberia, P. Chakraborty, S. Chandra, S. Chapeland, M. Chartier, S. Chattopadhyay, T. Cheng, C. Cheshkov, B. Cheynis, V. Chibante Barroso, D. D. Chinellato, E. S. Chizzali, J. Cho, S. Cho, P. Chochula, P. Christakoglou, C. H. Christensen, P. Christiansen, T. Chujo, M. Ciacco, C. Cicalo, F. Cindolo, M. R. Ciupek, G. Clai, F. Colamaria, J. S. Colburn, D. Colella, M. Colocci, M. Concas, G. Conesa Balbastre, Z. Conesa del Valle, G. Contin, J. G. Contreras, M. L. Coquet, T. M. Cormier, P. Cortese, M. R. Cosentino, F. Costa, S. Costanza, C. Cot, J. Crkovská, P. Crochet, R. Cruz-Torres, E. Cuautle, P. Cui, A. Dainese, M. C. Danisch, A. Danu, P. Das, S. Das, A. R. Dash, S. Dash, A. De Caro, G. de Cataldo, J. de Cuveland, A. De Falco, D. De Gruttola, N. De Marco, C. De Martin, S. De Pasquale, R. Deb, S. Deb, R. J. Debski, K. R. Deja, R. Del Grande, L. Dello Stritto, W. Deng, P. Dhankher, D. Di Bari, A. Di Mauro, R. A. Diaz, T. Dietel, Y. Ding, R. Divià, D. U. Dixit, Ø. Djuvsland, U. Dmitrieva, A. Dobrin, B. Dönigus, J. M. Dubinski, A. Dubla, S. Dudi, P. Dupieux, M. Durkac, N. Dzalaiova, T. M. Eder, R. J. Ehlers, V. N. Eikeland, F. Eisenhut, D. Elia, B. Erazmus, F. Ercolessi, F. Erhardt, M. R. Ersdal, B. Espagnon, G. Eulisse, D. Evans, S. Evdokimov, L. Fabbietti, M. Faggin, J. Faivre, F. Fan, W. Fan, A. Fantoni, M. Fasel, P. Fecchio, A. Feliciello, G. Feofilov, A. Fernández Téllez, L. Ferrandi, M. B. Ferrer, A. Ferrero, C. Ferrero, A. Ferretti, V. J. G. Feuillard, V. Filova, D. Finogeev, F. M. Fionda, F. Flor, A. N. Flores, S. Foertsch, I. Fokin, S. Fokin, E. Fragiacomo, E. Frajna, U. Fuchs, N. Funicello, C. Furget, A. Furs, T. Fusayasu, J. J. Gaardhøje, M. Gagliardi, A. M. Gago, C. D. Galvan, D. R. Gangadharan, P. Ganoti, C. Garabatos, T. García Chávez, E. Garcia-Solis, K. Garg, C. Gargiulo, K. Garner, P. Gasik, A. Gautam, M. B. Gay Ducati, M. Germain, A. Ghimouz, C. Ghosh, M. Giacalone, P. Giubellino, P. Giubilato, A. M. C. Glaenzer, P. Glässel, E. Glimos, D. J. Q. Goh, V. Gonzalez, L. H. González-Trueba, M. Gorgon, S. Gotovac, V. Grabski, L. K. Graczykowski, E. Grecka, A. Grelli, C. Grigoras, V. Grigoriev, S. Grigoryan, F. Grosa, J. F. Grosse-Oetringhaus, R. Grosso, D. Grund, G. G. Guardiano, R. Guernane, M. Guilbaud, K. Gulbrandsen, T. Gündem, T. Gunji, W. Guo, A. Gupta, R. Gupta, L. Gyulai, M. K. Habib, C. Hadjidakis, F. U. Haider, H. Hamagaki, A. Hamdi, M. Hamid, Y. Han, R. Hannigan, M. R. Haque, J. W. Harris, A. Harton, H. Hassan, D. Hatzifotiadou, P. Hauer, L. B. Havener, S. T. Heckel, E. Hellbär, H. Helstrup, M. Hemmer, T. Herman, G. Herrera Corral, F. Herrmann, S. Herrmann, K. F. Hetland, B. Heybeck, H. Hillemanns, C. Hills, B. Hippolyte, F. W. Hoffmann, B. Hofman, B. Hohlweger, G. H. Hong, M. Horst, A. Horzyk, Y. Hou, P. Hristov, C. Hughes, P. Huhn, L. M. Huhta, T. J. Humanic, A. Hutson, D. Hutter, J. P. Iddon, R. Ilkaev, H. Ilyas, M. Inaba, G. M. Innocenti, M. Ippolitov, A. Isakov, T. Isidori, M. S. Islam, M. Ivanov, V. Ivanov, M. Jablonski, B. Jacak, N. Jacazio, P. M. Jacobs, S. Jadlovska, J. Jadlovsky, S. Jaelani, L. Jaffe, C. Jahnke, M. J. Jakubowska, M. A. Janik, T. Janson, M. Jercic, S. Jia, A. A. P. Jimenez, F. Jonas, J. M. Jowett, J. Jung, M. Jung, A. Junique, A. Jusko, J. Kaewjai, P. Kalinak, A. S. Kalteyer, A. Kalweit, V. Kaplin, A. Karasu Uysal, D. Karatovic, O. Karavichev, T. Karavicheva, P. Karczmarczyk, E. Karpechev, M. J. Karwowska, U. Kebschull, R. Keidel, D. L. D. Keijdener, M. Keil, B. Ketzer, A. M. Khan, S. Khan, A. Khanzadeev, Y. Kharlov, A. Khatun, A. Khuntia, M. B. Kidson, B. Kileng, B. Kim, C. Kim, D. J. Kim, E. J. Kim, J. Kim, J. S. Kim, M. Kim, S. Kim, T. Kim, K. Kimura, S. Kirsch, I. Kisel, S. Kiselev, A. Kisiel, J. P. Kitowski, J. L. Klay, J. Klein, S. Klein, C. Klein-Bösing, M. Kleiner, T. Klemenz, A. Kluge, A. G. Knospe, C. Kobdaj, T. Kollegger, A. Kondratyev, N. Kondratyeva, E. Kondratyuk, J. Konig, S. A. Konigstorfer, P. J. Konopka, G. 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Yin, I.-K. Yoo, J. H. Yoon, S. Yuan, A. Yuncu, V. Zaccolo, C. Zampolli, F. Zanone, N. Zardoshti, A. Zarochentsev, P. Závada, N. Zaviyalov, M. Zhalov, B. Zhang, L. Zhang, M. Zhang, S. Zhang, X. Zhang, Y. Zhang, Z. Zhang, M. Zhao, V. Zherebchevskii, Y. Zhi, D. Zhou, Y. Zhou, J. Zhu, Y. Zhu, S. C. Zugravel, and N. Zurlo

Subjects
Heavy Ion Experiments, Jets, Particle Correlations and Fluctuations, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract The azimuthal anisotropy of particles associated with jets (jet particles) at midrapidity is measured for the first time in p-Pb and Pb-Pb collisions at s NN $$ \sqrt{{\textrm{s}}_{\textrm{NN}}} $$ = 5.02 TeV down to transverse momentum (p T) of 0.5 GeV/c and 2 GeV/c, respectively, with ALICE. The results obtained in p-Pb collisions are based on a novel three-particle correlation technique. The azimuthal anisotropy coefficient v 2 in high-multiplicity p-Pb collisions is positive, with a significance reaching 6.8σ at low p T, and its magnitude is smaller than in semicentral Pb-Pb collisions. In contrast to the measurements in Pb-Pb collisions, the v 2 coefficient is also found independent of p T within uncertainties. Comparisons with the inclusive charged-particle v 2 and with AMPT calculations are discussed. The predictions suggest that parton interactions play an important role in generating a non-zero jet-particle v 2 in p-Pb collisions, even though they overestimate the reported measurement. These observations shed new insights on the understanding of the origin of the collective behaviour of jet particles in small systems such as p-Pb collisions, and provide significant stringent new constraints to models.

Published
2024
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16. The ALICE experiment: a journey through QCD

Author

ALICE Collaboration, S. Acharya, D. Adamová, A. Adler, G. Aglieri Rinella, M. Agnello, N. Agrawal, Z. Ahammed, S. Ahmad, S. U. Ahn, I. Ahuja, A. Akindinov, M. Al-Turany, D. Aleksandrov, B. Alessandro, H. M. Alfanda, R. Alfaro Molina, B. Ali, A. Alici, N. Alizadehvandchali, A. Alkin, J. Alme, G. Alocco, T. Alt, I. Altsybeev, J. R. Alvarado, M. N. Anaam, C. Andrei, A. Andronic, V. Anguelov, F. Antinori, P. Antonioli, N. Apadula, L. Aphecetche, H. Appelshäuser, C. Arata, S. Arcelli, M. Aresti, R. Arnaldi, I. C. Arsene, M. Arslandok, A. Augustinus, R. Averbeck, M. D. Azmi, A. Badalà, J. Bae, Y. W. Baek, X. Bai, R. Bailhache, Y. Bailung, R. Bala, A. Balbino, A. Baldisseri, B. Balis, D. Banerjee, Z. Banoo, R. Barbera, F. Barile, L. Barioglio, M. Barlou, G. G. Barnaföldi, L. S. Barnby, V. Barret, L. Barreto, C. Bartels, K. Barth, E. Bartsch, N. Bastid, S. Basu, G. Batigne, D. Battistini, B. Batyunya, D. Bauri, J. L. Bazo Alba, I. G. Bearden, C. Beattie, P. Becht, D. Behera, I. Belikov, A. D. C. Bell Hechavarria, F. Bellini, R. Bellwied, S. Belokurova, V. Belyaev, G. Bencedi, S. Beole, A. Bercuci, Y. Berdnikov, A. Berdnikova, L. Bergmann, M. G. Besoiu, L. Betev, P. P. Bhaduri, A. Bhasin, M. A. Bhat, B. Bhattacharjee, L. Bianchi, N. Bianchi, J. Bielčík, J. Bielčíková, J. Biernat, A. P. Bigot, A. Bilandzic, G. Biro, S. Biswas, N. Bize, J. T. Blair, D. Blau, M. B. Blidaru, N. Bluhme, C. Blume, G. Boca, F. Bock, T. Bodova, A. Bogdanov, S. Boi, J. Bok, L. Boldizsár, A. Bolozdynya, M. Bombara, P. M. Bond, G. Bonomi, H. Borel, A. Borissov, A. G. Borquez Carcamo, H. Bossi, E. Botta, Y. E. M. Bouziani, L. Bratrud, P. Braun-Munzinger, M. Bregant, M. Broz, G. E. Bruno, M. D. Buckland, D. Budnikov, H. Buesching, S. Bufalino, O. Bugnon, P. Buhler, Z. Buthelezi, S. A. Bysiak, M. Cai, H. Caines, A. Caliva, E. Calvo Villar, J. M. M. Camacho, P. Camerini, F. D. M. Canedo, S. L. Cantway, M. Carabas, A. A. Carballo, F. Carnesecchi, R. Caron, L. A. D. Carvalho, J. Castillo Castellanos, A. J. 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Luparello, Y. G. Ma, A. Maevskaya, M. Mager, T. Mahmoud, A. Maire, R. D. Majka, M. V. Makariev, M. Malaev, G. Malfattore, N. M. Malik, Q. W. Malik, S. K. Malik, L. Malinina, D. Mal’Kevich, D. Mallick, N. Mallick, G. Mandaglio, V. Manko, F. Manso, V. Manzari, Y. Mao, G. V. Margagliotti, A. Margotti, A. Marín, C. Markert, P. Martinengo, J. L. Martinez, M. I. Martínez, G. Martínez García, S. Masciocchi, M. Masera, A. Masoni, L. Massacrier, A. Mastroserio, O. Matonoha, P. F. T. Matuoka, A. Matyja, C. Mayer, J. Mazer, A. L. Mazuecos, F. Mazzaschi, M. Mazzilli, J. E. Mdhluli, A. F. Mechler, Y. Melikyan, A. Menchaca-Rocha, E. Meninno, A. S. Menon, M. Meres, S. Mhlanga, Y. Miake, L. Micheletti, L. C. Migliorin, D. L. Mihaylov, K. Mikhaylov, A. N. Mishra, D. Miśkowiec, A. Modak, A. P. Mohanty, B. Mohanty, M. Mohisin Khan, M. A. Molander, Z. Moravcova, C. Mordasini, D. A. Moreira De Godoy, I. Morozov, A. Morsch, T. Mrnjavac, V. Muccifora, S. Muhuri, J. D. Mulligan, A. Mulliri, M. G. Munhoz, R. H. Munzer, H. Murakami, S. Murray, L. Musa, J. Musinsky, J. W. Myrcha, B. Naik, A. I. Nambrath, B. K. Nandi, R. Nania, E. Nappi, A. F. Nassirpour, A. Nath, C. Nattrass, T. K. Nayak, M. N. Naydenov, A. Neagu, A. Negru, L. Nellen, S. V. Nesbo, G. Neskovic, D. Nesterov, B. S. Nielsen, E. G. Nielsen, S. Nikolaev, S. Nikulin, V. Nikulin, F. Noferini, S. Noh, P. Nomokonov, J. Norman, N. Novitzky, P. Nowakowski, A. Nyanin, J. Nystrand, M. Ogino, A. Ohlson, V. A. Okorokov, J. Oleniacz, A. C. Oliveira Da Silva, M. H. Oliver, A. Onnerstad, C. Oppedisano, A. Ortiz Velasquez, J. Otwinowski, M. Oya, K. Oyama, Y. Pachmayer, S. Padhan, D. Pagano, G. Paić, S. Paisano-Guzmán, A. Palasciano, A. Palmeri, S. Panebianco, G. S. Pappalardo, H. Park, J. Park, J. E. Parkkila, R. N. Patra, B. Paul, H. Pei, T. Peitzmann, X. Peng, M. Pennisi, L. G. Pereira, H. Pereira Da Costa, D. Peresunko, G. M. Perez, S. Perrin, Y. Pestov, V. Petráček, V. Petrov, M. Petrovici, R. P. Pezzi, S. Piano, M. Pikna, P. Pillot, O. Pinazza, L. Pinsky, C. Pinto, S. Pisano, M. Płoskoń, M. Planinic, F. Pliquett, M. G. Poghosyan, B. Polichtchouk, S. Politano, N. Poljak, A. Pop, S. Porteboeuf-Houssais, V. Pozdniakov, K. K. Pradhan, S. K. Prasad, S. Prasad, R. Preghenella, F. Prino, C. A. Pruneau, I. Pshenichnov, M. Puccio, S. Pucillo, Z. Pugelova, S. Qiu, L. Quaglia, R. E. Quishpe, S. Ragoni, A. Rakotozafindrabe, L. Ramello, F. Rami, T. A. Rancien, M. Rasa, S. S. Räsänen, R. Rath, M. P. Rauch, I. Ravasenga, K. F. Read, C. Reckziegel, A. R. Redelbach, K. Redlich, C. A. Reetz, H. D. Regules-Medel, A. Rehman, F. Reidt, H. A. Reme-Ness, Z. Rescakova, K. Reygers, A. Riabov, V. Riabov, R. Ricci, M. Richter, A. A. Riedel, W. Riegler, F. Riggi, C. Ristea, M. Rodríguez Cahuantzi, S. A. Rodríguez Ramírez, K. Røed, R. Rogalev, E. Rogochaya, T. S. Rogoschinski, D. Rohr, D. Röhrich, P. F. Rojas, S. Rojas Torres, P. S. Rokita, G. Romanenko, F. Ronchetti, A. Rosano, E. D. Rosas, A. Rossi, A. Roy, S. Roy, N. Rubini, D. Ruggiano, R. Rui, B. Rumyantsev, P. G. Russek, R. Russo, A. Rustamov, E. Ryabinkin, Y. Ryabov, A. Rybicki, H. Rytkonen, W. Rzesa, O. A. M. Saarimaki, R. Sadek, S. Sadhu, S. Sadovsky, J. Saetre, K. Šafařík, S. K. Saha, S. Saha, B. Sahoo, R. Sahoo, S. Sahoo, D. Sahu, P. K. Sahu, J. Saini, K. Sajdakova, S. Sakai, M. P. Salvan, S. Sambyal, I. Sanna, T. B. Saramela, D. Sarkar, N. Sarkar, P. Sarma, V. Sarritzu, V. M. Sarti, M. H. P. Sas, J. Schambach, H. S. Scheid, C. Schiaua, R. Schicker, A. Schmah, C. Schmidt, H. R. Schmidt, M. O. Schmidt, M. Schmidt, N. V. Schmidt, A. R. Schmier, R. Schotter, A. Schröter, J. Schukraft, K. Schwarz, K. Schweda, G. Scioli, E. Scomparin, J. E. Seger, Y. Sekiguchi, D. Sekihata, I. Selyuzhenkov, S. Senyukov, J. J. Seo, D. Serebryakov, L. Šerkšnytė, A. Sevcenco, T. J. Shaba, A. Shabetai, R. Shahoyan, A. Shangaraev, A. Sharma, B. Sharma, D. Sharma, H. Sharma, M. Sharma, S. Sharma, U. Sharma, A. Shatat, O. Sheibani, K. Shigaki, M. Shimomura, J. Shin, S. Shirinkin, Q. Shou, Y. Sibiriak, S. Siddhanta, T. Siemiarczuk, T. F. Silva, D. Silvermyr, T. Simantathammakul, R. Simeonov, B. Singh, R. Singh, S. Singh, V. K. Singh, V. Singhal, T. Sinha, B. Sitar, M. Sitta, T. B. Skaali, G. Skorodumovs, M. Slupecki, N. Smirnov, R. J. M. Snellings, E. H. Solheim, J. Song, A. Songmoolnak, F. Soramel, S. P. Sorensen, R. Spijkers, I. Sputowska, J. Staa, J. Stachel, I. Stan, P. J. Steffanic, S. F. Stiefelmaier, D. Stocco, I. Storehaug, P. Stratmann, S. Strazzi, C. P. Stylianidis, A. A. P. Suaide, C. Suire, M. Sukhanov, M. Suljic, R. Sultanov, V. Sumberia, S. Sumowidagdo, S. Swain, I. Szarka, S. F. Taghavi, G. Taillepied, J. Takahashi, G. J. Tambave, S. Tang, Z. Tang, J. D. Tapia Takaki, N. Tapus, L. A. Tarasovicova, M. G. Tarzila, G. F. Tassielli, A. Tauro, A. Tavira García, G. Tejeda Muñoz, A. Telesca, L. Terlizzi, C. Terrevoli, G. Tersimonov, S. Thakur, D. Thomas, A. Tikhonov, A. R. Timmins, M. Tkacik, T. Tkacik, A. Toia, R. Tokumoto, N. Topilskaya, M. Toppi, F. Torales-Acosta, T. Tork, A. G. Torres Ramos, A. Trifiró, A. S. Triolo, S. Tripathy, T. Tripathy, S. Trogolo, V. Trubnikov, W. H. Trzaska, T. P. Trzcinski, A. Tumkin, R. Turrisi, T. S. Tveter, K. Ullaland, B. Ulukutlu, A. Uras, M. Urioni, G. L. Usai, M. Vala, N. Valle, L. V. R. van Doremalen, C. Van Hulse, M. van Leeuwen, C. A. van Veen, R. J. G. van Weelden, P. Vande Vyvre, D. Varga, Z. Varga, M. Vasileiou, A. Vasiliev, O. Vázquez Doce, O. Vazquez Rueda, V. Vechernin, E. Vercellin, S. Vergara Limón, L. Vermunt, R. Vértesi, M. Verweij, L. Vickovic, Z. Vilakazi, O. Villalobos Baillie, G. Vino, A. Vinogradov, T. Virgili, V. Vislavicius, A. Vodopyanov, B. Volkel, M. A. Völkl, K. Voloshin, S. A. Voloshin, G. Volpe, B. von Haller, I. Vorobyev, N. Vozniuk, J. Vrláková, C. Wang, D. Wang, Y. Wang, M. Weber, A. Wegrzynek, F. T. Weiglhofer, S. C. Wenzel, J. P. Wessels, J. Wiechula, J. Wikne, G. Wilk, J. Wilkinson, G. A. Willems, B. Windelband, M. Winn, J. R. Wright, W. Wu, Y. Wu, R. Xu, A. Yadav, A. K. Yadav, S. Yalcin, Y. Yamaguchi, S. Yang, S. Yano, Z. Yin, I.-K. Yoo, J. H. Yoon, S. Yuan, A. Yuncu, V. Zaccolo, C. Zampolli, F. Zanone, N. Zardoshti, A. Zarochentsev, P. Závada, N. Zaviyalov, M. Zhalov, B. Zhang, L. Zhang, S. Zhang, X. Zhang, Y. Zhang, Z. Zhang, M. Zhao, V. Zherebchevskii, Y. Zhi, D. Zhou, Y. Zhou, J. Zhu, Y. Zhu, S. C. Zugravel, and N. Zurlo

Subjects
Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Abstract The ALICE experiment was proposed in 1993, to study strongly-interacting matter at extreme energy densities and temperatures. This proposal entailed a comprehensive investigation of nuclear collisions at the LHC. Its physics programme initially focused on the determination of the properties of the quark–gluon plasma (QGP), a deconfined state of quarks and gluons, created in such collisions. The ALICE physics programme has been extended to cover a broader ensemble of observables related to Quantum Chromodynamics (QCD), the theory of strong interactions. The experiment has studied Pb–Pb, Xe–Xe, p–Pb and pp collisions in the multi-TeV centre of mass energy range, during the Run 1–2 data-taking periods at the LHC (2009–2018). The aim of this review is to summarise the key ALICE physics results in this endeavor, and to discuss their implications on the current understanding of the macroscopic and microscopic properties of strongly-interacting matter at the highest temperatures reached in the laboratory. It will review the latest findings on the properties of the QGP created by heavy-ion collisions at LHC energies, and describe the surprising QGP-like effects in pp and p–Pb collisions. Measurements of few-body QCD interactions, and their impact in unraveling the structure of hadrons and hadronic interactions, will be discussed. ALICE results relevant for physics topics outside the realm of QCD will also be touched upon. Finally, prospects for future measurements with the ALICE detector in the context of its planned upgrades will also be briefly described.

Published
2024
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17. The rates of starch depletion and hydraulic failure both play a role in drought-induced seedling mortality

Author

Santiago Trueba, Noelia González Muñoz, Régis Burlett, Laurent J. Lamarque, Yves Gibon, Teresa E. Gimeno, Aurore Kaisermann, Camille Benard, Cédric Lemaire, Jose M. Torres-Ruiz, Lisa Wingate, and Sylvain Delzon

Subjects
Embolism vulnerability, Fructose, Nonstructural carbohydrates, Hydraulic safety margin, Light environment, Sucrose, Forestry, SD1-669.5
Abstract

Abstract Key message The elapsed times to deplete starch concentrations and to reach a null hydraulic safety margin were related to tree seedling mortality under experimental drought. Starch concentration showed an accelerated decline across all species during the early stages of dehydration, while the concentrations of soluble sugars and total nonstructural carbohydrates remained stable. Concomitant carbohydrate depletion and hydraulic failure drive seedling mortality under drought. Context Current upsurges of drought events are provoking impacts on tree physiology, resulting in forest mortality. Hydraulic dysfunction and nonstructural carbohydrate (NSC) depletion have been posited as the main mechanisms leading to plant mortality under drought. Aims This study explores the dynamics of the two mortality-inducing processes during drought stress using an experimental approach with 12 evergreen tree species. Methods Seedlings were subjected to drought until 100% mortality was observed. Midday (ΨMD) and predawn (ΨPD) water potentials, xylem pressure leading to a 50% loss of hydraulic conductivity (Ψ50), along with NSC concentrations in different organs (leaves, stems, and roots) were measured regularly during drought. Results Total NSC concentrations and soluble sugar pools did not decline during drought. However, starch pools showed strong reductions early during drought stress as ΨPD decreased, and the time leading to starch depletion emerged as a strong mortality predictor. Ψ50 alone did not provide an accurate estimate of mortality, while the elapsed time to reach a null hydraulic safety margin (ΨMD—Ψ50 = 0) was related to seedling mortality. Conclusion Adopting a dynamic approach by estimating the times to consume both starch reserves and hydraulic safety margins is highly relevant to improve predictions of tree mortality under the current context of increasing global drought.

Published
2024
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18. Exploring the role of plant hydraulics in canopy fuel moisture content: insights from an experimental drought study on Pinus halepensis Mill. and Quercus ilex L.

Author

Coffi Belmys Cakpo, Julien Ruffault, Jean-Luc Dupuy, François Pimont, Claude Doussan, Myriam Moreno, Nathan Jean, Frederic Jean, Regis Burlett, Sylvain Delzon, Santiago Trueba, José M. Torres-Ruiz, Hervé Cochard, and Nicolas Martin-StPaul

Subjects
Live fuel moisture content, Wildfire danger, Mediterranean, Mortality, Tree defoliation, Cavitation, Forestry, SD1-669.5
Abstract

Abstract Key Message Understanding the impact of extreme drought on the canopy fuel moisture content (CFMC) is crucial to anticipate the effects of climate change on wildfires. Our study demonstrates that foliage mortality, caused by leaf embolism, can substantially diminish CFMC during drought on Pinus halepensis Mill. and Quercus ilex L. It emphasizes the importance of considering plant hydraulics to improve wildfire predictions. Context Canopy fuel moisture content (CFMC), which represents the water-to-dry mass ratio in leaves and fine twigs within the canopy, is a major factor of fire danger across ecosystems worldwide. CFMC results from the fuel moisture content of living foliage (live fuel moisture content, LFMC) and dead foliage (dead fuel moisture content, DFMC) weighted by the proportion of foliage mortality in the canopy (α Dead ). Understanding how LFMC, α Dead , and ultimately CFMC are affected during extreme drought is essential for effective wildfire planning. Aims We aimed to understand how plant hydraulics affect CFMC for different levels of soil water deficit, examining its influence on both LFMC and α Dead . Methods We conducted a drought experiment on seedlings of two Mediterranean species: Aleppo pine (Pinus halepensis Mill.) and Holm oak (Quercus ilex L.). Throughout the drought experiment and after rewatering, we monitored CFMC, LFMC, and α Dead along with other ecophysiological variables. Results LFMC exhibited a significant decrease during drought, and as leaf water potentials reached low levels, α Dead increased in both species, thereby reducing CFMC. Distinct water use strategies resulted in species-specific variations in dehydration dynamics. Conclusion Our findings demonstrate that as drought conditions intensify, foliage mortality might become a critical physiological factor driving the decline in CFMC.

Published
2024
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19. Azimuthal anisotropy of jet particles in p-Pb and Pb-Pb collisions at sNN = 5.02 TeV

Author

Acharya, S., Adamová, D., Adler, A., Aglieri Rinella, G., Agnello, M., Agrawal, N., Ahammed, Z., Ahmad, S., Ahn, S. U., Ahuja, I., Akindinov, A., Al-Turany, M., Aleksandrov, D., Alessandro, B., Alfanda, H. M., Alfaro Molina, R., Ali, B., Alici, A., Alizadehvandchali, N., Alkin, A., Alme, J., Alocco, G., Alt, T., Altsybeev, I., Alvarado, J. R., Anaam, M. N., Andrei, C., Andronic, A., Anguelov, V., Antinori, F., Antonioli, P., Apadula, N., Aphecetche, L., Appelshäuser, H., Arata, C., Arcelli, S., Aresti, M., Arnaldi, R., Arneiro, J. G. M. C. A., Arsene, I. C., Arslandok, M., Augustinus, A., Averbeck, R., Azmi, M. D., Badalà, A., Bae, J., Baek, Y. W., Bai, X., Bailhache, R., Bailung, Y., Balbino, A., Baldisseri, A., Balis, B., Banerjee, D., Banoo, Z., Barbera, R., Barile, F., Barioglio, L., Barlou, M., Barnaföldi, G. G., Barnby, L. S., Barret, V., Barreto, L., Bartels, C., Barth, K., Bartsch, E., Bastid, N., Basu, S., Batigne, G., Battistini, D., Batyunya, B., Bauri, D., Bazo Alba, J. L., Bearden, I. G., Beattie, C., Becht, P., Behera, D., Belikov, I., Bell Hechavarria, A. D. C., Bellini, F., Bellwied, R., Belokurova, S., Belyaev, V., Bencedi, G., Beole, S., Berdnikov, Y., Berdnikova, A., Bergmann, L., Besoiu, M. G., Betev, L., Bhaduri, P. P., Bhasin, A., Bhat, M. A., Bhattacharjee, B., Bianchi, L., Bianchi, N., Bielčík, J., Bielčíková, J., Biernat, J., Bigot, A. P., Bilandzic, A., Biro, G., Biswas, S., Bize, N., Blair, J. T., Blau, D., Blidaru, M. B., Bluhme, N., Blume, C., Boca, G., Bock, F., Bodova, T., Bogdanov, A., Boi, S., Bok, J., Boldizsár, L., Bombara, M., Bond, P. M., Bonomi, G., Borel, H., Borissov, A., Borquez Carcamo, A. G., Bossi, H., Botta, E., Bouziani, Y. E. M., Bratrud, L., Braun-Munzinger, P., Bregant, M., Broz, M., Bruno, G. E., Buckland, M. D., Budnikov, D., Buesching, H., Bufalino, S., Bugnon, O., Buhler, P., Buthelezi, Z., Bysiak, S. A., Cai, M., Caines, H., Caliva, A., Calvo Villar, E., Camacho, J. M. M., Camerini, P., Canedo, F. D. M., Cantway, S. L., Carabas, M., Carballo, A. A., Carnesecchi, F., Caron, R., Carvalho, L. A. D., Castillo Castellanos, J., Catalano, F., Ceballos Sanchez, C., Chakaberia, I., Chakraborty, P., Chandra, S., Chapeland, S., Chartier, M., Chattopadhyay, S., Chattopadhyay, S., Cheng, T., Cheshkov, C., Cheynis, B., Chibante Barroso, V., Chinellato, D. D., Chizzali, E. S., Cho, J., Cho, S., Chochula, P., Christakoglou, P., Christensen, C. H., Christiansen, P., Chujo, T., Ciacco, M., Cicalo, C., Cindolo, F., Ciupek, M. R., Clai, G., Colamaria, F., Colburn, J. S., Colella, D., Colocci, M., Concas, M., Conesa Balbastre, G., Conesa del Valle, Z., Contin, G., Contreras, J. G., Coquet, M. L., Cormier, T. M., Cortese, P., Cosentino, M. R., Costa, F., Costanza, S., Cot, C., Crkovská, J., Crochet, P., Cruz-Torres, R., Cuautle, E., Cui, P., Dainese, A., Danisch, M. C., Danu, A., Das, P., Das, P., Das, S., Dash, A. R., Dash, S., De Caro, A., de Cataldo, G., de Cuveland, J., De Falco, A., De Gruttola, D., De Marco, N., De Martin, C., De Pasquale, S., Deb, R., Deb, S., Debski, R. J., Deja, K. R., Del Grande, R., Dello Stritto, L., Deng, W., Dhankher, P., Di Bari, D., Di Mauro, A., Diaz, R. A., Dietel, T., Ding, Y., Divià, R., Dixit, D. U., Djuvsland, Ø., Dmitrieva, U., Dobrin, A., Dönigus, B., Dubinski, J. M., Dubla, A., Dudi, S., Dupieux, P., Durkac, M., Dzalaiova, N., Eder, T. M., Ehlers, R. J., Eikeland, V. N., Eisenhut, F., Elia, D., Erazmus, B., Ercolessi, F., Erhardt, F., Ersdal, M. R., Espagnon, B., Eulisse, G., Evans, D., Evdokimov, S., Fabbietti, L., Faggin, M., Faivre, J., Fan, F., Fan, W., Fantoni, A., Fasel, M., Fecchio, P., Feliciello, A., Feofilov, G., Fernández Téllez, A., Ferrandi, L., Ferrer, M. B., Ferrero, A., Ferrero, C., Ferretti, A., Feuillard, V. J. G., Filova, V., Finogeev, D., Fionda, F. M., Flor, F., Flores, A. N., Foertsch, S., Fokin, I., Fokin, S., Fragiacomo, E., Frajna, E., Fuchs, U., Funicello, N., Furget, C., Furs, A., Fusayasu, T., Gaardhøje, J. J., Gagliardi, M., Gago, A. M., Galvan, C. D., Gangadharan, D. R., Ganoti, P., Garabatos, C., García Chávez, T., Garcia-Solis, E., Garg, K., Gargiulo, C., Garner, K., Gasik, P., Gautam, A., Gay Ducati, M. B., Germain, M., Ghimouz, A., Ghosh, C., Giacalone, M., Giubellino, P., Giubilato, P., Glaenzer, A. M. C., Glässel, P., Glimos, E., Goh, D. J. Q., Gonzalez, V., González-Trueba, L. H., Gorgon, M., Gotovac, S., Grabski, V., Graczykowski, L. K., Grecka, E., Grelli, A., Grigoras, C., Grigoriev, V., Grigoryan, S., Grosa, F., Grosse-Oetringhaus, J. F., Grosso, R., Grund, D., Guardiano, G. G., Guernane, R., Guilbaud, M., Gulbrandsen, K., Gündem, T., Gunji, T., Guo, W., Gupta, A., Gupta, R., Gyulai, L., Habib, M. K., Hadjidakis, C., Haider, F. U., Hamagaki, H., Hamdi, A., Hamid, M., Han, Y., Hannigan, R., Haque, M. R., Harris, J. 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2024
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20. The ALICE experiment: a journey through QCD

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Acharya, S., Adamová, D., Adler, A., Aglieri Rinella, G., Agnello, M., Agrawal, N., Ahammed, Z., Ahmad, S., Ahn, S. U., Ahuja, I., Akindinov, A., Al-Turany, M., Aleksandrov, D., Alessandro, B., Alfanda, H. M., Alfaro Molina, R., Ali, B., Alici, A., Alizadehvandchali, N., Alkin, A., Alme, J., Alocco, G., Alt, T., Altsybeev, I., Alvarado, J. R., Anaam, M. N., Andrei, C., Andronic, A., Anguelov, V., Antinori, F., Antonioli, P., Apadula, N., Aphecetche, L., Appelshäuser, H., Arata, C., Arcelli, S., Aresti, M., Arnaldi, R., Arsene, I. C., Arslandok, M., Augustinus, A., Averbeck, R., Azmi, M. D., Badalà, A., Bae, J., Baek, Y. W., Bai, X., Bailhache, R., Bailung, Y., Bala, R., Balbino, A., Baldisseri, A., Balis, B., Banerjee, D., Banoo, Z., Barbera, R., Barile, F., Barioglio, L., Barlou, M., Barnaföldi, G. G., Barnby, L. S., Barret, V., Barreto, L., Bartels, C., Barth, K., Bartsch, E., Bastid, N., Basu, S., Batigne, G., Battistini, D., Batyunya, B., Bauri, D., Bazo Alba, J. L., Bearden, I. G., Beattie, C., Becht, P., Behera, D., Belikov, I., Bell Hechavarria, A. D. C., Bellini, F., Bellwied, R., Belokurova, S., Belyaev, V., Bencedi, G., Beole, S., Bercuci, A., Berdnikov, Y., Berdnikova, A., Bergmann, L., Besoiu, M. G., Betev, L., Bhaduri, P. P., Bhasin, A., Bhat, M. A., Bhattacharjee, B., Bianchi, L., Bianchi, N., Bielčík, J., Bielčíková, J., Biernat, J., Bigot, A. P., Bilandzic, A., Biro, G., Biswas, S., Bize, N., Blair, J. T., Blau, D., Blidaru, M. B., Bluhme, N., Blume, C., Boca, G., Bock, F., Bodova, T., Bogdanov, A., Boi, S., Bok, J., Boldizsár, L., Bolozdynya, A., Bombara, M., Bond, P. M., Bonomi, G., Borel, H., Borissov, A., Borquez Carcamo, A. G., Bossi, H., Botta, E., Bouziani, Y. E. M., Bratrud, L., Braun-Munzinger, P., Bregant, M., Broz, M., Bruno, G. E., Buckland, M. D., Budnikov, D., Buesching, H., Bufalino, S., Bugnon, O., Buhler, P., Buthelezi, Z., Bysiak, S. A., Cai, M., Caines, H., Caliva, A., Calvo Villar, E., Camacho, J. M. M., Camerini, P., Canedo, F. D. M., Cantway, S. L., Carabas, M., Carballo, A. A., Carnesecchi, F., Caron, R., Carvalho, L. A. D., Castillo Castellanos, J., Castro, A. J., Catalano, F., Ceballos Sanchez, C., Chakaberia, I., Chakraborty, P., Chandra, S., Chapeland, S., Chartier, M., Chattopadhyay, S., Chattopadhyay, S., Cheng, T., Cheshkov, C., Cheynis, B., Chibante Barroso, V., Chinellato, D. D., Chizzali, E. S., Cho, J., Cho, S., Chochula, P., Christakoglou, P., Christensen, C. H., Christiansen, P., Chujo, T., Ciacco, M., Cicalo, C., Cindolo, F., Ciupek, M. R., Clai, G., Colamaria, F., Colburn, J. S., Colella, D., Colocci, M., Concas, M., Conesa Balbastre, G., Conesa del Valle, Z., Contin, G., Contreras, J. G., Coquet, M. L., Cormier, T. M., Cortese, P., Cosentino, M. R., Costa, F., Costanza, S., Cot, C., Crkovská, J., Crochet, P., Cruz-Torres, R., Cuautle, E., Cui, P., Dainese, A., Damas, F. P. A., Danisch, M. C., Danu, A., Das, D., Das, P., Das, P., Das, S., Dash, A. R., Dash, S., De Caro, A., de Cataldo, G., de Cuveland, J., De Falco, A., De Gruttola, D., De Marco, N., De Martin, C., De Pasquale, S., Deb, S., Debski, R. J., Deja, K. R., Del Grande, R., Dello Stritto, L., Deng, W., Dhankher, P., Di Bari, D., Di Mauro, A., Diab, B., Diaz, R. A., Dietel, T., Ding, Y., Divià, R., Dixit, D. U., Djuvsland, Ø., Dmitrieva, U., Dobrin, A., Dönigus, B., Dubinski, J. M., Dubla, A., Dudi, S., Dupieux, P., Durkac, M., Dzalaiova, N., Eder, T. M., Ehlers, R. J., Eikeland, V. N., Eisenhut, F., Elia, D., Erazmus, B., Ercolessi, F., Erhardt, F., Ersdal, M. R., Espagnon, B., Eulisse, G., Evans, D., Evdokimov, S., Fabbietti, L., Faggin, M., Faivre, J., Fan, F., Fan, W., Fantoni, A., Fasel, M., Fecchio, P., Feliciello, A., Feofilov, G., Fernández Téllez, A., Ferrandi, L., Ferrer, M. B., Ferrero, A., Ferrero, C., Ferretti, A., Feuillard, V. J. G., Filova, V., Finogeev, D., Fionda, F. M., Flor, F., Flores, A. N., Foertsch, S., Fokin, I., Fokin, S., Fragiacomo, E., Frajna, E., Fuchs, U., Funicello, N., Furget, C., Furs, A., Fusayasu, T., Gaardhøje, J. J., Gagliardi, M., Gago, A. M., Gallio, M., Galvan, C. D., Gangadharan, D. R., Ganoti, P., Garabatos, C., García Chávez, T., Garcia-Solis, E., Garg, K., Gargiulo, C., Garner, K., Gasik, P., Gauger, E. F., Gautam, A., Gay Ducati, M. B., Germain, M., Ghosh, C., Giacalone, M., Giubellino, P., Giubilato, P., Glaenzer, A. M. C., Glässel, P., Glimos, E., Goh, D. J. Q., Gonzalez, V., González-Trueba, L. H., Gorgon, M., Gotovac, S., Grabski, V., Graczykowski, L. K., Grecka, E., Grelli, A., Grigoras, C., Grigoriev, V., Grigoryan, S., Grosa, F., Grosse-Oetringhaus, J. F., Grosso, R., Grund, D., Guardiano, G. G., Guernane, R., Guilbaud, M., Gulbrandsen, K., Gündem, T., Gunji, T., Guo, W., Gupta, A., Gupta, R., Gyulai, L., Habib, M. K., Hadjidakis, C., Haider, F. U., Hamagaki, H., Hamdi, A., Hamid, M., Han, Y., Hannigan, R., Haque, M. R., Harris, J. W., Harton, A., Hassan, H., Hatzifotiadou, D., Hauer, P., Havener, L. B., Heckel, S. T., Hellbär, E., Helstrup, H., Hemmer, M., Herman, T., Herrera Corral, G., Herrmann, F., Herrmann, S., Hetland, K. F., Heybeck, B., Hillemanns, H., Hills, C., Hippolyte, B., Hofman, B., Hohlweger, B., Hong, G. H., Horst, M., Horzyk, A., Hosokawa, R., Hou, Y., Hristov, P., Hughes, C., Huhn, P., Huhta, L. M., Humanic, T. J., Hutson, A., Hutter, D., Iddon, J. P., Ilkaev, R., Ilyas, H., Inaba, M., Innocenti, G. M., Ippolitov, M., Isakov, A., Isidori, T., Islam, M. S., Ivanov, M., Ivanov, M., Ivanov, V., Jablonski, M., Jacak, B., Jacazio, N., Jacobs, P. M., Jadlovska, S., Jadlovsky, J., Jaelani, S., Jaffe, L., Jahnke, C., Jakubowska, M. J., Janik, M. A., Janson, T., Jercic, M., Jia, S., Jimenez, A. A. P., Jonas, F., Jowett , J. M., Jung, J., Jung, M., Junique, A., Jusko, A., Kaewjai, J., Kalinak, P., Kalteyer, A. S., Kalweit, A., Kaplin, V., Karasu Uysal, A., Karatovic, D., Karavichev, O., Karavicheva, T., Karczmarczyk, P., Karpechev, E., Karwowska, M. J., Kebschull, U., Keidel, R., Keijdener, D. L. D., Keil, M., Ketzer, B., Khan, A. M., Khan, S., Khanzadeev, A., Kharlov, Y., Khatun, A., Khuntia, A., Kidson, M. B., Kileng, B., Kim, B., Kim, C., Kim, D. J., Kim, E. J., Kim, J., Kim, J. S., Kim, J., Kim, J., Kim, M., Kim, S., Kim, T., Kimura, K., Kirsch, S., Kisel, I., Kiselev, S., Kisiel, A., Kitowski, J. P., Klay, J. L., Klein, J., Klein, S., Klein-Bösing, C., Kleiner, M., Klemenz, T., Kluge, A., Knospe, A. G., Kobdaj, C., Kollegger, T., Kondratyev, A., Kondratyeva, N., Kondratyuk, E., Konig, J., Konigstorfer, S. A., Konopka, P. J., Kornakov, G., Korwieser, M., Koryciak, S. D., Kotliarov, A., Kovalenko, V., Kowalski, M., Kozhuharov, V., Králik, I., Kravčáková, A., Kreis, L., Krivda, M., Krizek, F., Gajdosova, K. Krizkova, Kroesen, M., Krüger, M., Krupova, D. M., Kryshen, E., Kučera, V., Kuhn, C., Kuijer, P. G., Kumaoka, T., Kumar, D., Kumar, L., Kumar, N., Kumar, S., Kundu, S., Kurashvili, P., Kurepin, A., Kurepin, A. B., Kuryakin, A., Kushpil, S., Kvapil, J., Kweon, M. J., Kwon, J. Y., Kwon, Y., La Pointe, S. L., La Rocca, P., Lai, Y. S., Lakrathok, A., Lamanna, M., Langoy, R., Larionov, P., Laudi, E., Lautner, L., Lavicka, R., Lazareva, T., Lea, R., Lee, H., Legras, G., Lehrbach, J., Lemmon, R. C., León Monzón, I., Lesch, M. M., Lesser, E. D., Lettrich, M., Lévai, P., Li, X., Li, X. L., Lien, J., Lietava, R., Lim, B., Lim, S. H., Lindenstruth, V., Lindner, A., Lippmann, C., Liu, A., Liu, D. H., Liu, J., Lofnes, I. M., Loizides, C., Lokos, S., Lömker, J., Loncar, P., Lopez, J. A., Lopez, X., López Torres, E., Lu, P., Luhder, J. R., Lunardon, M., Luparello, G., Ma, Y. G., Maevskaya, A., Mager, M., Mahmoud, T., Maire, A., Majka, R. D., Makariev, M. V., Malaev, M., Malfattore, G., Malik, N. M., Malik, Q. W., Malik, S. K., Malinina, L., Mal’Kevich, D., Mallick, D., Mallick, N., Mandaglio, G., Manko, V., Manso, F., Manzari, V., Mao, Y., Margagliotti, G. V., Margotti, A., Marín, A., Markert, C., Martinengo, P., Martinez, J. L., Martínez, M. I., Martínez García, G., Masciocchi, S., Masera, M., Masoni, A., Massacrier, L., Mastroserio, A., Matonoha, O., Matuoka, P. F. T., Matyja, A., Mayer, C., Mazer, J., Mazuecos, A. L., Mazzaschi, F., Mazzilli, M., Mdhluli, J. E., Mechler, A. F., Melikyan, Y., Menchaca-Rocha, A., Meninno, E., Menon, A. S., Meres, M., Mhlanga, S., Miake, Y., Micheletti, L., Migliorin, L. C., Mihaylov, D. L., Mikhaylov, K., Mishra, A. N., Miśkowiec, D., Modak, A., Mohanty, A. P., Mohanty, B., Mohisin Khan, M., Molander, M. A., Moravcova, Z., Mordasini, C., Moreira De Godoy, D. A., Morozov, I., Morsch, A., Mrnjavac, T., Muccifora, V., Muhuri, S., Mulligan, J. D., Mulliri, A., Munhoz, M. G., Munzer, R. H., Murakami, H., Murray, S., Musa, L., Musinsky, J., Myrcha, J. W., Naik, B., Nambrath, A. I., Nandi, B. K., Nania, R., Nappi, E., Nassirpour, A. F., Nath, A., Nattrass, C., Nayak, T. K., Naydenov, M. N., Neagu, A., Negru, A., Nellen, L., Nesbo, S. V., Neskovic, G., Nesterov, D., Nielsen, B. S., Nielsen, E. G., Nikolaev, S., Nikulin, S., Nikulin, V., Noferini, F., Noh, S., Nomokonov, P., Norman, J., Novitzky, N., Nowakowski, P., Nyanin, A., Nystrand, J., Ogino, M., Ohlson, A., Okorokov, V. A., Oleniacz, J., Oliveira Da Silva, A. C., Oliver, M. H., Onnerstad, A., Oppedisano, C., Ortiz Velasquez, A., Otwinowski, J., Oya, M., Oyama, K., Pachmayer, Y., Padhan, S., Pagano, D., Paić, G., Paisano-Guzmán, S., Palasciano, A., Palmeri, A., Panebianco, S., Pappalardo, G. S., Park, H., Park, H., Park, J., Parkkila, J. E., Patra, R. N., Paul, B., Pei, H., Peitzmann, T., Peng, X., Pennisi, M., Pereira, L. G., Pereira Da Costa, H., Peresunko, D., Perez, G. M., Perrin, S., Pestov, Y., Petráček, V., Petrov, V., Petrovici, M., Pezzi, R. P., Piano, S., Pikna, M., Pillot, P., Pinazza, O., Pinsky, L., Pinto, C., Pisano, S., Płoskoń, M., Planinic, M., Pliquett, F., Poghosyan, M. G., Polichtchouk, B., Politano, S., Poljak, N., Pop, A., Porteboeuf-Houssais, S., Pozdniakov, V., Pradhan, K. K., Prasad, S. K., Prasad, S., Preghenella, R., Prino, F., Pruneau, C. A., Pshenichnov, I., Puccio, M., Pucillo, S., Pugelova, Z., Qiu, S., Quaglia, L., Quishpe, R. E., Ragoni, S., Rakotozafindrabe, A., Ramello, L., Rami, F., Rancien, T. A., Rasa, M., Räsänen, S. S., Rath, R., Rauch, M. P., Ravasenga, I., Read, K. F., Reckziegel, C., Redelbach, A. R., Redlich, K., Reetz, C. A., Regules-Medel, H. D., Rehman, A., Reidt, F., Reme-Ness, H. A., Rescakova, Z., Reygers, K., Riabov, A., Riabov, V., Ricci, R., Richter, M., Riedel, A. A., Riegler, W., Riggi, F., Ristea, C., Rodríguez Cahuantzi, M., Rodríguez Ramírez, S. A., Røed, K., Rogalev, R., Rogochaya, E., Rogoschinski, T. S., Rohr, D., Röhrich, D., Rojas, P. F., Rojas Torres, S., Rokita, P. S., Romanenko, G., Ronchetti, F., Rosano, A., Rosas, E. D., Rossi, A., Roy, A., Roy, S., Rubini, N., Ruggiano, D., Rui, R., Rumyantsev, B., Russek, P. G., Russo, R., Rustamov, A., Ryabinkin, E., Ryabov, Y., Rybicki, A., Rytkonen, H., Rzesa, W., Saarimaki, O. A. M., Sadek, R., Sadhu, S., Sadovsky, S., Saetre, J., Šafařík, K., Saha, S. K., Saha, S., Sahoo, B., Sahoo, R., Sahoo, S., Sahu, D., Sahu, P. K., Saini, J., Sajdakova, K., Sakai, S., Salvan, M. P., Sambyal, S., Sanna, I., Saramela, T. B., Sarkar, D., Sarkar, N., Sarma, P., Sarritzu, V., Sarti, V. M., Sas, M. H. P., Schambach, J., Scheid, H. S., Schiaua, C., Schicker, R., Schmah, A., Schmidt, C., Schmidt, H. R., Schmidt, M. O., Schmidt, M., Schmidt, N. V., Schmier, A. R., Schotter, R., Schröter, A., Schukraft, J., Schwarz, K., Schweda, K., Scioli, G., Scomparin, E., Seger, J. E., Sekiguchi, Y., Sekihata, D., Selyuzhenkov, I., Senyukov, S., Seo, J. J., Serebryakov, D., Šerkšnytė, L., Sevcenco, A., Shaba, T. J., Shabetai, A., Shahoyan, R., Shangaraev, A., Sharma, A., Sharma, B., Sharma, D., Sharma, H., Sharma, M., Sharma, S., Sharma, S., Sharma, U., Shatat, A., Sheibani, O., Shigaki, K., Shimomura, M., Shin, J., Shirinkin, S., Shou, Q., Sibiriak, Y., Siddhanta, S., Siemiarczuk, T., Silva, T. F., Silvermyr, D., Simantathammakul, T., Simeonov, R., Singh, B., Singh, B., Singh, R., Singh, R., Singh, R., Singh, S., Singh, V. K., Singhal, V., Sinha, T., Sitar, B., Sitta, M., Skaali, T. B., Skorodumovs, G., Slupecki, M., Smirnov, N., Snellings, R. J. M., Solheim, E. H., Song, J., Songmoolnak, A., Soramel, F., Sorensen, S. P., Spijkers, R., Sputowska, I., Staa, J., Stachel, J., Stan, I., Steffanic, P. J., Stiefelmaier, S. F., Stocco, D., Storehaug, I., Stratmann, P., Strazzi, S., Stylianidis, C. P., Suaide, A. A. P., Suire, C., Sukhanov, M., Suljic, M., Sultanov, R., Sumberia, V., Sumowidagdo, S., Swain, S., Szarka, I., Taghavi, S. F., Taillepied, G., Takahashi, J., Tambave, G. J., Tang, S., Tang, Z., Tapia Takaki, J. D., Tapus, N., Tarasovicova, L. A., Tarzila, M. G., Tassielli, G. F., Tauro, A., Tavira García, A., Tejeda Muñoz, G., Telesca, A., Terlizzi, L., Terrevoli, C., Tersimonov, G., Thakur, S., Thomas, D., Tikhonov, A., Timmins, A. R., Tkacik, M., Tkacik, T., Toia, A., Tokumoto, R., Topilskaya, N., Toppi, M., Torales-Acosta, F., Tork, T., Torres Ramos, A. G., Trifiró, A., Triolo, A. S., Tripathy, S., Tripathy, T., Trogolo, S., Trubnikov, V., Trzaska, W. H., Trzcinski, T. P., Tumkin, A., Turrisi, R., Tveter, T. S., Ullaland, K., Ulukutlu, B., Uras, A., Urioni, M., Usai, G. L., Vala, M., Valle, N., van Doremalen, L. V. R., Van Hulse, C., van Leeuwen, M., van Veen, C. A., van Weelden, R. J. G., Vande Vyvre, P., Varga, D., Varga, Z., Vasileiou, M., Vasiliev, A., Vázquez Doce, O., Vazquez Rueda, O., Vechernin, V., Vercellin, E., Vergara Limón, S., Vermunt, L., Vértesi, R., Verweij, M., Vickovic, L., Vilakazi, Z., Villalobos Baillie, O., Vino, G., Vinogradov, A., Virgili, T., Vislavicius, V., Vodopyanov, A., Volkel, B., Völkl, M. A., Voloshin, K., Voloshin, S. A., Volpe, G., von Haller, B., Vorobyev, I., Vozniuk, N., Vrláková, J., Wang, C., Wang, D., Wang, Y., Weber, M., Wegrzynek, A., Weiglhofer, F. T., Wenzel, S. C., Wessels, J. P., Wiechula, J., Wikne, J., Wilk, G., Wilkinson, J., Willems, G. A., Windelband, B., Winn, M., Wright, J. R., Wu, W., Wu, Y., Xu, R., Yadav, A., Yadav, A. K., Yalcin, S., Yamaguchi, Y., Yang, S., Yano, S., Yin, Z., Yoo, I.-K., Yoon, J. H., Yuan, S., Yuncu, A., Zaccolo, V., Zampolli, C., Zanone, F., Zardoshti, N., Zarochentsev, A., Závada, P., Zaviyalov, N., Zhalov, M., Zhang, B., Zhang, L., Zhang, S., Zhang, X., Zhang, Y., Zhang, Z., Zhao, M., Zherebchevskii, V., Zhi, Y., Zhou, D., Zhou, Y., Zhu, J., Zhu, Y., Zugravel, S. C., and Zurlo, N.

Published
2024
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21. Atrous Space Bender U-Net (ASBU-Net/LogiNet)

Author

Bansal, Anurag, Ostap, Oleg, Trueba, Miguel Maestre, and Perry, Kristopher

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

$ $With recent advances in CNNs, exceptional improvements have been made in semantic segmentation of high resolution images in terms of accuracy and latency. However, challenges still remain in detecting objects in crowded scenes, large scale variations, partial occlusion, and distortions, while still maintaining mobility and latency. We introduce a fast and efficient convolutional neural network, ASBU-Net, for semantic segmentation of high resolution images that addresses these problems and uses no novelty layers for ease of quantization and embedded hardware support. ASBU-Net is based on a new feature extraction module, atrous space bender layer (ASBL), which is efficient in terms of computation and memory. The ASB layers form a building block that is used to make ASBNet. Since this network does not use any special layers it can be easily implemented, quantized and deployed on FPGAs and other hardware with limited memory. We present experiments on resource and accuracy trade-offs and show strong performance compared to other popular models.

Published
2022

22. Collagen IV deficiency causes hypertrophic remodeling and endothelium-dependent hyperpolarization in small vessel disease with intracerebral hemorrhageResearch in context

Author

Sarah McNeilly, Cameron R. Thomson, Laura Gonzalez-Trueba, Yuan Yan Sin, Alessandra Granata, Graham Hamilton, Michelle Lee, Erin Boland, John D. McClure, Cristina Lumbreras-Perales, Alisha Aman, Apoorva A. Kumar, Marco Cantini, Caglar Gök, Delyth Graham, Yasuko Tomono, Christopher D. Anderson, Yinhui Lu, Colin Smith, Hugh S. Markus, Marc Abramowicz, Catheline Vilain, Rustam Al-Shahi Salman, Manuel Salmeron-Sanchez, Atticus H. Hainsworth, William Fuller, Karl E. Kadler, Neil J. Bulleid, and Tom Van Agtmael

Subjects
Collagen, Basement membrane, Cerebrovascular disease, Stroke, Small vessel disease, Endothelial dysfunction, Medicine, Medicine (General), R5-920
Abstract

Summary: Background: Genetic variants in COL4A1 and COL4A2 (encoding collagen IV alpha chain 1/2) occur in genetic and sporadic forms of cerebral small vessel disease (CSVD), a leading cause of stroke, dementia and intracerebral haemorrhage (ICH). However, the molecular mechanisms of CSVD with ICH and COL4A1/COL4A2 variants remain obscure. Methods: Vascular function and molecular investigations in mice with a Col4a1 missense mutation and heterozygous Col4a2 knock-out mice were combined with analysis of human brain endothelial cells harboring COL4A1/COL4A2 mutations, and brain tissue of patients with sporadic CSVD with ICH. Findings: Col4a1 missense mutations cause early-onset CSVD independent of hypertension, with enhanced vasodilation of small arteries due to endothelial dysfunction, vascular wall thickening and reduced stiffness. Mechanistically, the early-onset dysregulated endothelium-dependent hyperpolarization (EDH) is due to reduced collagen IV levels with elevated activity and levels of endothelial Ca2+-sensitive K+ channels. This results in vasodilation via the Na/K pump in vascular smooth muscle cells. Our data support this endothelial dysfunction preceding development of CSVD-associated ICH is due to increased cytoplasmic Ca2+ levels in endothelial cells. Moreover, cerebral blood vessels of patients with sporadic CSVD show genotype-dependent mechanisms with wall thickening and lower collagen IV levels in those harboring common non-coding COL4A1/COL4A2 risk alleles. Interpretation: COL4A1/COL4A2 variants act in genetic and sporadic CSVD with ICH via dysregulated EDH, and altered vascular wall thickness and biomechanics due to lower collagen IV levels and/or mutant collagen IV secretion. These data highlight EDH and collagen IV levels as potential treatment targets. Funding: MRC, Wellcome Trust, BHF.

Published
2024
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23. Progress on levitating a sphere in cryogenic fluids

Author

Arrayás, Manuel, Bettsworth, Francis, Haley, Richard, Schanen, Roch, Trueba, José Luis, Uriarte, Carlos, Zavyalov, Vladislav, and Zmeev, Dmitry

Subjects
Condensed Matter - Superconductivity
Abstract

We present the working prototype of a levitation system designed for investigation of flows in cryogenic helium fluids. The current device allows the levitation of a superconducting sphere and has several provisions made for allowing precise control over its motion. We report on progress in the detection and control systems of the prototype and demonstrate how uniform circular motion can be implemented., Comment: 13 pages, 7 figures

Published
2022
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26. Low-data? No problem: low-resource, language-agnostic conversational text-to-speech via F0-conditioned data augmentation

Author

Comini, Giulia, Huybrechts, Goeric, Ribeiro, Manuel Sam, Gabrys, Adam, and Lorenzo-Trueba, Jaime

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound
Abstract

The availability of data in expressive styles across languages is limited, and recording sessions are costly and time consuming. To overcome these issues, we demonstrate how to build low-resource, neural text-to-speech (TTS) voices with only 1 hour of conversational speech, when no other conversational data are available in the same language. Assuming the availability of non-expressive speech data in that language, we propose a 3-step technology: 1) we train an F0-conditioned voice conversion (VC) model as data augmentation technique; 2) we train an F0 predictor to control the conversational flavour of the voice-converted synthetic data; 3) we train a TTS system that consumes the augmented data. We prove that our technology enables F0 controllability, is scalable across speakers and languages and is competitive in terms of naturalness over a state-of-the-art baseline model, another augmented method which does not make use of F0 information., Comment: Accepted for presentation at Interspeech 2022

Published
2022

27. Computer-assisted Pronunciation Training -- Speech synthesis is almost all you need

Author

Korzekwa, Daniel, Lorenzo-Trueba, Jaime, Drugman, Thomas, and Kostek, Bozena

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Machine Learning
Abstract

The research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high accuracy (only 60\% precision at 40\%-80\% recall). One of the key problems is the low availability of mispronounced speech that is needed for the reliable training of pronunciation error detection models. If we had a generative model that could mimic non-native speech and produce any amount of training data, then the task of detecting pronunciation errors would be much easier. We present three innovative techniques based on phoneme-to-phoneme (P2P), text-to-speech (T2S), and speech-to-speech (S2S) conversion to generate correctly pronounced and mispronounced synthetic speech. We show that these techniques not only improve the accuracy of three machine learning models for detecting pronunciation errors but also help establish a new state-of-the-art in the field. Earlier studies have used simple speech generation techniques such as P2P conversion, but only as an additional mechanism to improve the accuracy of pronunciation error detection. We, on the other hand, consider speech generation to be the first-class method of detecting pronunciation errors. The effectiveness of these techniques is assessed in the tasks of detecting pronunciation and lexical stress errors. Non-native English speech corpora of German, Italian, and Polish speakers are used in the evaluations. The best proposed S2S technique improves the accuracy of detecting pronunciation errors in AUC metric by 41\% from 0.528 to 0.749 compared to the state-of-the-art approach., Comment: Published in Speech Communication Journal

Published
2022
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28. Evaluation of changes in the faecal resistome associated with children's exposure to domestic animals and food animal production

Author

Cifuentes, Sara G, Graham, Jay, Loayza, Fernanda, Saraiva, Carlos, Salinas, Liseth, Trueba, Gabriel, and Cárdenas, Paúl A

Subjects
Genetics, Antimicrobial Resistance, Pediatric, 2.2 Factors relating to the physical environment, Aetiology, Zero Hunger, Animals, Drug Resistance, Bacterial, Metagenomics, Animals, Domestic, Feces, Anti-Bacterial Agents, Anti-Infective Agents, Gut resistome, Children, Domestic animals, Food animal production, Ecuador
Abstract

ObjectivesThe paediatric gut microbiota is a reservoir of antimicrobial resistance genes. Environmental factors such as a child's exposure to faecal contamination and antimicrobial resistance genes of animal origin likely shape the resistome of infants and children. This study measured how different levels of exposure to domestic or food animals affect the structure of the intestinal resistome in children between 1 and 7 years of age.MethodsOne hundred nineteen faecal samples from 39 children were analysed according to the level of exposure to domestic or food animals and categorized into three risk groups. Using high-throughput sequencing with an Illumina NovaSeq 6000 SP platform, we performed faecal resistome analyses using the ResFinder database. Additionally, ResistoXplorer was used to characterize the resistomes of children differentially exposed to domestic animals.ResultsOur data indicated that specific antimicrobial resistance genes such as those that confer resistance to MATFPR (macrolide, aminoglycoside, tetracycline, fluoroquinolone, phenicol, and rifamycin) and tetracyclines were statistically less abundant in the group of children without exposure to animals (group 2), compared with the groups exposed to domestic and food animals (groups 1 and 3). However, the overall resistome structure among the children was not affected by the different levels of exposure to animals.ConclusionsThis study suggests that animal exposure is a risk factor for young children acquiring specific antimicrobial resistance genes from domestic animals or animal production areas. However, the overall resistome structure was not affected.

Published
2022

29. Plasma concentrations of IL-6, MIP-1β, IP-10, and PTX-3 as predictors of the immunological response to antiretroviral treatment in people with HIV

Author

Marta Mejías-Trueba, Abraham Saborido-Alconchel, Ana Serna-Gallego, María Trujillo-Rodríguez, Esperanza Muñoz-Muela, Silvia Llaves-Flores, Nuria Espinosa, Cristina Roca-Oporto, Marta Herrero, Cesar Sotomayor, and Luis F. López-Cortes

Subjects
HIV infection, IL-6, IP-10, MIP-1β, PTX-3, immunologic response, Immunologic diseases. Allergy, RC581-607
Abstract

Despite effective antiretroviral therapy (ART), 15-30% of people with HIV experience poor CD4+ T-cell recovery, termed immunologic non-responders (INR). This study aims to evaluate whether pre-ART plasma levels of interleukin-6 (IL-6), interferon gamma-induced protein-10 (IP-10), macrophage inflammatory protein-1-β (MIP-1β), and/or pentraxin-3 (PTX-3) could predict subsequent immunologic recovery. Seventy-four participants were enrolled and classified as INR and immunologic responders (IR) based on CD4+/CD8+ ratio increase over 24 months after starting ART. The results showed no significant differences in cytokine levels between INR and IR. Therefore, IL-6, IP-10, MIP-1β, and PTX-3 were unsuitable as predictive markers of poor immune recovery.

Published
2024
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30. Usos y sentidos del peculio en las colocaciones asistenciales de menores de edad. Provincia de Buenos Aires, comienzos del siglo XX

Author

Yolanda De Paz Trueba

Subjects
trabajo, infancias, servicio doméstico, peculio, History of Civilization, CB3-482, History (General) and history of Europe, Latin America. Spanish America, F1201-3799, Industry, HD2321-4730.9, Labor. Work. Working class, HD4801-8943, Social history and conditions. Social problems. Social reform, HN1-995
Abstract

Este artículo busca brindar un panorama complejo de los mundos laborales de las infancias, atendiendo a las colocaciones asistenciales en casas de familia y comercios. Con las herramientas que brinda la historia social del trabajo, proponemos un acercamiento a la manera en que el dinero y otras formas de pago atravesaron estas relaciones, y a los sentidos que le dieron quienes formaron parte de ese vínculo. Estas formas de trabajo y las diversas maneras de remunerarlas, persistieron en paralelo con el avance de cierta mercantilización del mundo laboral doméstico formal contratado en el mercado libremente e, incluso, con los intentos de regular el trabajo de menores de edad.

Published
2024
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31. Long-term effectiveness, safety, and tolerability of doravirine in antiretroviral-experienced people with HIV in real life

Author

Marta Mejías-Trueba, Alicia Gutierrez-Valencia, Silvia Llaves-Flores, Cristina Roca-Oporto, Marta Herrero, César Sotomayor de la Piedra, Luis F. Lopez-Cortes, and Nuria Espinosa

Subjects
HIV cure, ARV, viral supression, treatment, Microbiology, QR1-502
Abstract

ABSTRACT Real-life data on doravirine (DOR) in different drug combinations are limited. We evaluated the effectiveness of DOR plus two nucleos(t)ide reverse transcriptase inhibitors (NRTI), mainly abacavir/lamivudine, and dual therapies in people with HIV (PWH), mostly virologically suppressed. Ambispective observational study that enrolled adults PWH who initiated a DOR-based regimen from September 2020 to February 2022 at a referral center in Spain. Participants were grouped as follows: A, received DOR plus two NRTI; B, dual therapy (DT) with DOR plus dolutegravir (DTG) or darunavir/cobicistat (DRVc); C, DOR plus ≥two antiretroviral drugs. The primary endpoints were treatment effectiveness at week 48 by intention-to-treat (ITT) and per-protocol analysis (OT). A cohort of 187 participants, 91% virologically suppressed, were analyzed after a median follow-up of 112 weeks (80–136). Group A received DOR plus abacavir/lamivudine (ABV/3TC) (n = 109) or tenofovir/emtricitabine (TFV/3TC) (n = 45). At week 48, the effectiveness of DOR plus ABV/3TC by ITT was 90.8% (CI95, 88.0–93.6), better than with TFV/FTC [73.3% (66.7–79.9); P = 0.003]. Only one virologic failure was observed. Mild adverse effects were the cause of treatment discontinuation in 7.8%, followed by switching to a single-tablet regimen. In group B, the effectiveness by ITT was 92.9% (CI95, 88.0–97.8) at week 48. No adverse effects or virologic failure were registered in this group. DOR plus two NRTI or DT have long-term effectiveness and safety as a switching option for PWH, mostly virologically suppressed. The DOR plus ABV/3TC combination has shown even better effectiveness than TFV/FTC.IMPORTANCEDOR-based regimens have shown long-term effectiveness and safety in PWH, mostly virologically suppressed. The combination of DOR plus ABV/3TC has shown even better safety and effectiveness than TFV/FTC. DOR plus two NRTI offers cost benefits compared to other regimens.

Published
2024
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32. Engrosamiento del receso axilar glenohumeral como signo ecográfico de capsulitis adhesiva

Author

Ricardo H. Trueba, Augusto Napoli, and Agustín Marrero

Subjects
Hombro. Capsulitis adhesiva. Ecografía. Resonancia magnética., Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

En el período de la pandemia de COVID-19 hemos visto en las consultas un incremento de los casos de capsulitis adhesiva (CA). Los pacientes se presentaban con dolor de hombro asociado a una limitación en los movimientos de rotación externa y abducción. Los criterios clínicos se consideran el estándar para el diagnóstico, siendo la resonancia magnética (RM) una excelente herramienta para su diagnóstico imagenológico. Los hallazgos típicos son engrosamiento y cambios en la intensidad de señal de la cápsula articular en el receso axilar y en el intervalo rotador, así como engrosamiento del ligamento coracohumeral (LCH). El examen ecográfico es discutido y solo unos pocos estudios han tratado de probar su precisión, basados en la evaluación del engrosamiento del LCH y el aumento de la vascularización en el intervalo rotador. Recientemente se ha propuesto la medición de la cápsula del receso axilar como signo ecográfico de CA, permitiendo un análisis fácil y posible durante una exploración comparativa bilateral. Un grosor superior a 2,0 mm en la cápsula del receso axilar medido en la ecografía se correlacionó con signos de CA en la RM. En todos los casos que evaluamos durante este período observamos la misma correlación.

Published
2024
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33. Classification of radiological patterns of tuberculosis with a Convolutional neural network in x-ray images

Author

Adrian Trueba Espinosa, Jessica Sanchez -Arrazola, Jair Cervantes, Farid Garcia-Lamont, and José Sergio Ruiz Castilla

Subjects
Tuberculosis patterns, Convolutional neural networks, Chest X-rays, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95
Abstract

In this paper we propose the classification of radiological patterns with the presence of tuberculosis in X-ray images, it was observed that two to six patterns (consolidation, fibrosis, opacity, opacity, pleural, nodules and cavitations) are present in the radiographs of the patients. It is important to mention that species specialists consider the type of TB pattern in order to provide appropriate treatment. It should be noted that not all medical centres have specialists who can immediately interpret radiological patterns. Considering the above, the aim is to classify patterns by means of a convolutional neural network to help make a more accurate diagnosis on X-rays, so that doctors can recommend immediate treatment and thus avoid infecting more people. For the classification of tuberculosis patterns, a proprietary convolutional neural network (CNN) was proposed and compared against the VGG16, InceptionV3 and ResNet-50 architectures, which were selected based on the results of other radiograph classification research [1]–[3] . The results obtained for the Macro-averange AUC-SVM metric for the proposed architecture and InceptionV3 were 0.80, and for VGG16 it was 0.75, and for the ResNet-50 network it was 0.79. The proposed architecture has better classification results, as does InceptionV3.

Published
2024
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34. Efficacy assessment of liposome crosslinked hyaluronic acid and standard hyaluronic acid eye drops for dry eye disease management: a comparative study employing the ocular surface analyzer and subjective questionnaires

Author

José-María Sánchez-González, Concepción De-Hita-Cantalejo, María Luisa González-Rodríguez, Ana Fernández-Trueba-Fagúndez, Antonio Ballesteros-Sánchez, Clara Martinez-Perez, Romina Caro-Díaz, Carla Montiel Guzman, María Fernanda González-Oyarce, and María Carmen Sánchez-González

Subjects
crosslinked hyaluronic acid, hyaluronic acid, dry eye disease, liposome, lipid layer, tear film stability, Medicine (General), R5-920
Abstract

IntroductionDry eye disease (DED) is a prevalent condition causing ocular discomfort and visual disturbances, often managed with artificial tears. This study aimed to assess and compare the efficacy of eye drops containing Crosslinked Hyaluronic Acid (CHA) with liposomes and crocin and standard Hyaluronic Acid (HA) for DED management.MethodsA single-blind, longitudinal study was conducted on 24 participants (48 eyes), randomized to receive one of the two treatments. Ocular health measures, including the ocular surface disease index (OSDI) and the standard patient evaluation of eye dryness (SPEED) scores, were assessed at baseline and 6 weeks post-treatment using the Ocular Surface Analyzer.ResultsCHA achieved a lipid layer thickness increase of 1.29 ± 1.08 Guillon pattern degree (p < 0.01), FNIBUT increase 0.64 ± 0.77 s (p < 0.01), MNIBUT increase1.28 ± 4.74 s (p = 0.19), OSDI decrease 11.72 ± 6.73 score points (p < 0.01) and SPEED decrease 1.16 ± 5.05 score points (p = 0.27). Significant reductions in the OSDI and SPEED scores post-treatment were observed with both treatments, indicating their effectiveness.ConclusionCHA with liposomes exhibits superior efficacy compared to standard HA eye drops in the management of DED. These findings highlight the potential for personalized treatment strategies incorporating CHA, indicating a more effective approach to DED management. However, further research is required to validate these results and investigate the long-term effects, which may pave the way for a data-driven and optimized approach to managing DED.

Published
2024
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35. El mercado de valores, una herramienta de acceso y dispersión de la riqueza

Author

Edgar Trueba Paz y Puente

Subjects
mercado de valores, redistribución, riqueza, capitalismo, globalización, Law
Abstract

En los últimos años se han desarrollado diversos cuestionamientos al modelo capitalista. Uno de los más recurrentes se centra en el incremento de la desigualdad y la necesidad de redistribución de la riqueza. En este ensayo se cuestionan algunos planeamientos de la propuesta redistributiva y se sugiere que, en su lugar, la discusión debiera enfocarse en el acceso a la riqueza. Asimismo, se plantea que los mercados financieros, particularmente el mercado de valores, son una herramienta útil en lograr un mayor acceso y dispersión de la riqueza.

Published
2024
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36. SHREC 2021: Classification in cryo-electron tomograms

Author

Gubins, Ilja, Chaillet, Marten L., van der Schot, Gijs, Trueba, M. Cristina, Veltkamp, Remco C., Förster, Friedrich, Wang, Xiao, Kihara, Daisuke, Moebel, Emmanuel, Nguyen, Nguyen P., White, Tommi, Bunyak, Filiz, Papoulias, Giorgos, Gerolymatos, Stavros, Zacharaki, Evangelia I., Moustakas, Konstantinos, Zeng, Xiangrui, Liu, Sinuo, Xu, Min, Wang, Yaoyu, Chen, Cheng, Cui, Xuefeng, and Zhang, Fa

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Cryo-electron tomography (cryo-ET) is an imaging technique that allows three-dimensional visualization of macro-molecular assemblies under near-native conditions. Cryo-ET comes with a number of challenges, mainly low signal-to-noise and inability to obtain images from all angles. Computational methods are key to analyze cryo-electron tomograms. To promote innovation in computational methods, we generate a novel simulated dataset to benchmark different methods of localization and classification of biological macromolecules in tomograms. Our publicly available dataset contains ten tomographic reconstructions of simulated cell-like volumes. Each volume contains twelve different types of complexes, varying in size, function and structure. In this paper, we have evaluated seven different methods of finding and classifying proteins. Seven research groups present results obtained with learning-based methods and trained on the simulated dataset, as well as a baseline template matching (TM), a traditional method widely used in cryo-ET research. We show that learning-based approaches can achieve notably better localization and classification performance than TM. We also experimentally confirm that there is a negative relationship between particle size and performance for all methods., Comment: Workshop version of the paper can be found here: https://diglib.eg.org/handle/10.2312/3dor20211307

Published
2022
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37. ‘My appetite and mind would go’: Inuit perceptions of (im)mobility and wellbeing loss under climate change across Inuit Nunangat in the Canadian Arctic

Author

Sonja Ayeb-Karlsson, Anna Hoad, and Mei L. Trueba

Subjects
History of scholarship and learning. The humanities, AZ20-999, Social Sciences
Abstract

Abstract The academic literature on personal experiences of climate-induced wellbeing erosion (often conceptualised as ‘non-economic losses and damages’) is still limited. This represents a serious climate policy gap that hinders support for marginalised people across the world including Indigenous People. Lately, we have seen a rapid growth in empirical studies exploring linkages between climate change and mental health among Indigenous Inuit in Canada. However, its association with human (im)mobility remains unexplored. This review article brings together the empirical evidence of Inuit experiences and perceptions of climate-related wellbeing loss and (im)mobility while providing climate policy with guidance for appropriate action. The systematic review investigates how Inuit in Arctic Canada felt that climatic changes impacted their (im)mobility and mental health while putting these feelings into a wider context of colonial violence, forced child removal, the residential schools, and other systematic human rights abuses. Twelve electronic databases (four specific to Arctic research) were searched for English and French, peer reviewed, qualitative studies published between 2000 and 2021. Fifteen selected articles were analysed using NVivo and thematic narrative analysis from a climate-violence-health nexus systems approach. Three overarching climate-related wellbeing loss themes, all strongly intertwined with feelings of immobility, emerged from the literature namely ‘identity and cultural loss’, ‘land connection as a source of healing’, and ‘changing environment triggering emotional distress’. The narratives circled around Inuit land connection and how climate-induced temporary (im)mobility interrupted this relationship. Climatic changes isolated Inuit away from the land and cut off their ability to partake in land activities. This strongly eroded Inuit wellbeing, expressed through distress, anxiety, depression, social tension, suicide ideation and deep feelings of cultural loss. The findings showed how Inuit mental health strongly depend on a sustained connection to the land. Further empirical research among other Indigenous People or nomadic groups on wellbeing loss and climate-induced involuntary immobility is urgently needed. Future research should particularly explore how such mental health impacts tie into past and present (post)colonial traumas and current suicide occurrences. This will help climate policy, research, and adaptation planning better prepare and propose more contextually and culturally appropriate health actions in the future.

Published
2024
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38. Voice Filter: Few-shot text-to-speech speaker adaptation using voice conversion as a post-processing module

Author

Gabryś, Adam, Huybrechts, Goeric, Ribeiro, Manuel Sam, Chien, Chung-Ming, Roth, Julian, Comini, Giulia, Barra-Chicote, Roberto, Perz, Bartek, and Lorenzo-Trueba, Jaime

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

State-of-the-art text-to-speech (TTS) systems require several hours of recorded speech data to generate high-quality synthetic speech. When using reduced amounts of training data, standard TTS models suffer from speech quality and intelligibility degradations, making training low-resource TTS systems problematic. In this paper, we propose a novel extremely low-resource TTS method called Voice Filter that uses as little as one minute of speech from a target speaker. It uses voice conversion (VC) as a post-processing module appended to a pre-existing high-quality TTS system and marks a conceptual shift in the existing TTS paradigm, framing the few-shot TTS problem as a VC task. Furthermore, we propose to use a duration-controllable TTS system to create a parallel speech corpus to facilitate the VC task. Results show that the Voice Filter outperforms state-of-the-art few-shot speech synthesis techniques in terms of objective and subjective metrics on one minute of speech on a diverse set of voices, while being competitive against a TTS model built on 30 times more data., Comment: Accepted at ICASSP 2022

Published
2022

39. Cross-speaker style transfer for text-to-speech using data augmentation

Author

Ribeiro, Manuel Sam, Roth, Julian, Comini, Giulia, Huybrechts, Goeric, Gabrys, Adam, and Lorenzo-Trueba, Jaime

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Computation and Language, Computer Science - Machine Learning, Computer Science - Sound
Abstract

We address the problem of cross-speaker style transfer for text-to-speech (TTS) using data augmentation via voice conversion. We assume to have a corpus of neutral non-expressive data from a target speaker and supporting conversational expressive data from different speakers. Our goal is to build a TTS system that is expressive, while retaining the target speaker's identity. The proposed approach relies on voice conversion to first generate high-quality data from the set of supporting expressive speakers. The voice converted data is then pooled with natural data from the target speaker and used to train a single-speaker multi-style TTS system. We provide evidence that this approach is efficient, flexible, and scalable. The method is evaluated using one or more supporting speakers, as well as a variable amount of supporting data. We further provide evidence that this approach allows some controllability of speaking style, when using multiple supporting speakers. We conclude by scaling our proposed technology to a set of 14 speakers across 7 languages. Results indicate that our technology consistently improves synthetic samples in terms of style similarity, while retaining the target speaker's identity., Comment: 5 pages, 3 figures, 4 tables. ICASSP 2022

Published
2022

41. A longitudinal study of dominant E. coli lineages and antimicrobial resistance in the gut of children living in an upper middle-income country

Author

Calderón, Diana, Cárdenas, Paúl A, Prado-Vivar, Belen, Graham, Jay P, and Trueba, Gabriel

Subjects
Clinical Research, Antimicrobial Resistance, Pediatric, Infectious Diseases, Digestive Diseases, 2.2 Factors relating to the physical environment, Aetiology, Infection, Anti-Bacterial Agents, Drug Resistance, Bacterial, Ecosystem, Escherichia coli, Humans, Longitudinal Studies, Microbial Sensitivity Tests, Prospective Studies, beta-Lactamases, Numerically dominant strains, E. coli, longitudinal, Antimicrobial resistance, Ecuador, ST131, E. coli, longitudinal
Abstract

ObjectivesThe gastrointestinal tract constitutes a complex and diverse ecosystem. Escherichia coli is one of the most frequently studied and characterised species in the gut ecosystem; nevertheless, there has been little research to determine their diversity and population dynamics in the intestines of children over time. We analysed the turnover or dominant E. coli isolates in children faecal matter during 1 year.MethodsIn this prospective study, a fresh faecal sample was obtained from children longitudinally over one year (30 faecal samples at sampling period 1 and 22 faecal samples at sampling periods 2 and 3). From each stool sample, five E. coli colonies were randomly selected (n = 405 E. coli isolates total) in order to characterize the genotype and phenotypic antimicrobial resistance patterns.ResultsWe were unable to find same E. coli dominant clone in faecal matter from 30 children in different sampling periods. Whole-genome sequencing of three isolates belonging to ST131 found in one child during the sampling period I and II indicated that isolates were three different ST 131 clones that carried extended-spectrum β-lactamase (ESBL) genes.ConclusionWe found that all numerically dominant E. coli lineages in children's intestines were transient colonisers, and antimicrobial resistance phenotypes of these strains varied significantly over time without any apparent selective force.

Published
2022

42. The Appeal of Tai Chi and Complementary Therapies for College Students with Adhd

Author

Sulzer, Sandra H., Trueba, Cathleen, and Converse, Alexander K.

Abstract

Background: Developing effective non-pharmacological therapies for Attention Deficit Hyperactivity Disorder (ADHD) is important. We gauged the likelihood that undergraduates would participate in a trial of tai chi as an intervention for ADHD, and evaluated attitudes toward complementary and alternative medicine (CAM). Methods: We collected survey responses from 47 undergraduates with ADHD and 49 healthy controls, measuring their likelihood of participating in trials of tai chi and other non-pharmacological therapies, along with attitudes toward CAM. We examined the relationship between diagnosis, CAM attitudes, and willingness to participate in a trial. Results: Undergraduates with ADHD showed greater acceptance of CAM therapies. Thirty two percent of students with ADHD expressed strong willingness to participate in a tai chi trial. Conclusion: These results support the feasibility of a trial of tai chi as therapy for undergraduates with ADHD, and suggest this population is receptive toward CAM. Future research should examine why interest in CAM is greater among students with ADHD.

Published
2023
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43. Levitating frogs, machine learning and elliptic integrals

Author

Arrayás, M., Trueba, J. L., and Uriarte, C.

Subjects
Physics - Computational Physics
Abstract

We present the calculation of the stability region of a perfect diamagnet levitated in a magnetic field created by a circular current loop. We make use of the machine learning technique of automatic differentiation to illustrate the calculations with the elliptic integrals involved.

Published
2021

44. A Spectroscopic Angle on Central Engine Size Scales in Accreting Neutron Stars

Author

Trueba, Nicolas, Miller, J. M., Fabian, A. C., Kaastra, J., Kallman, T., Lohfink, A., Ludlam, R. M., Proga, D., Raymond, J., Reynolds, C., Reynolds, M., and Zoghbi, A.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Analyses of absorption from disk winds and atmospheres in accreting compact objects typically treat the central emitting regions in these systems as point sources relative to the absorber. This assumption breaks down if the absorbing gas is located within $few \times 1000\cdot GM/{c}^{2}$, in which case a small component of the absorber's Keplerian motion contributes to the velocity-width of absorption lines. Here, we demonstrate how this velocity-broadening effect can be used to constrain the sizes of central engines in accreting compact objects via a simple geometric relationship, and develop a method for modeling this effect. We apply this method on the Chandra/HETG spectra of three ultra-compact and short period neutron star X-ray binaries in which evidence of gravitationally redshifted absorption, owing to an inner-disk atmosphere, has recently been reported. The significance of the redshift is above $5\sigma$ for XTE J1710$-$281 (this work) and 4U 1916$-$053, and is inconsistent with various estimates of the relative radial velocity of each binary. For our most sensitive spectrum (XTE J1710$-$281), we obtain a 1$\sigma$ upper bound of 310 $\text{km}$ $\text{s}^{-1}$ on the magnitude of this geometric effect and a central engine of size ${R}_{CE} < 60 ~ GM/{c}^{2}$ (or, $< 90 ~ GM/{c}^{2}$ at the $3\sigma$ level). These initial constraints compare favorably to those obtained via microlensing in quasars and approach the sensitivity of constraints via relativistic reflection in neutron stars. This sensitivity will increase with further exposures, as well as the launch of future microcalorimeter and grating missions., Comment: Accepted to ApJ, 32 Pages (3 Appendices), 17 Figures

Published
2021
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45. Comparison of metagenomic and traditional methods for diagnosis of E. coli enteric infections

Author

C. Royer, N. V. Patin, K. J. Jesser, A. Peña-Gonzalez, J. K. Hatt, G. Trueba, K. Levy, and K. T. Konstantinidis

Subjects
diarrhea, diagnostics, metagenomics, E. coli, Microbiology, QR1-502
Abstract

ABSTRACTDiarrheagenic Escherichia coli, collectively known as DEC, is a leading cause of diarrhea, particularly in children in low- and middle-income countries. Diagnosing infections caused by different DEC pathotypes traditionally relies on the cultivation and identification of virulence genes, a resource-intensive and error-prone process. Here, we compared culture-based DEC identification with shotgun metagenomic sequencing of whole stool using 35 randomly drawn samples from a cohort of diarrhea-afflicted patients. Metagenomic sequencing detected the cultured isolates in 97% of samples, revealing, overall, reliable detection by this approach. Genome binning yielded high-quality E. coli metagenome-assembled genomes (MAGs) for 13 samples, and we observed that the MAG did not carry the diagnostic DEC virulence genes of the corresponding isolate in 60% of these samples. Specifically, two distinct scenarios were observed: diffusely adherent E. coli (DAEC) isolates without corresponding DAEC MAGs appeared to be relatively rare members of the microbiome, which was further corroborated by quantitative PCR (qPCR), and thus unlikely to represent the etiological agent in 3 of the 13 samples (~23%). In contrast, ETEC virulence genes were located on plasmids and largely escaped binning in associated MAGs despite being prevalent in the sample (5/13 samples or ~38%), revealing limitations of the metagenomic approach. These results provide important insights for diagnosing DEC infections and demonstrate how metagenomic methods can complement isolation efforts and PCR for pathogen identification and population abundance.IMPORTANCEDiagnosing enteric infections based on traditional methods involving isolation and PCR can be erroneous due to isolation and other biases, e.g., the most abundant pathogen may not be recovered on isolation media. By employing shotgun metagenomics together with traditional methods on the same stool samples, we show that mixed infections caused by multiple pathogens are much more frequent than traditional methods indicate in the case of acute diarrhea. Further, in at least 8.5% of the total samples examined, the metagenomic approach reliably identified a different pathogen than the traditional approach. Therefore, our results provide a methodology to complement existing methods for enteric infection diagnostics with cutting-edge, culture-independent metagenomic techniques, and highlight the strengths and limitations of each approach.

Published
2024
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46. Endogenous origin of Pseudomonas aeruginosa infecting hospitalized patients in Ecuador

Author

Gabriela Vasco, Mishell Achig, Belén Prado-Vivar, Maritza Páez, Franklin Espinosa, Evelyn Espinoza, Danny Quinancela, Paul Cardenas, and Gabriel Trueba

Subjects
Pseudomonas aeruginosa, Nosocomial, Colonization, Acute infection, Whole genome sequencing, Infectious and parasitic diseases, RC109-216, Public aspects of medicine, RA1-1270
Abstract

Summary: Recent evidence suggests that Pseudomonas aeruginosa, a bacterium that has the ability to cause deadly infections in hospitalized patients, could originate in the patient's own flora. We employed the Oxford Nanopore platform to obtain whole genome sequences (WGS) from clinical and rectal screen P. aeruginosa strains belonging to 15 patients from two hospitals. Our study found evidence that clinical and rectal isolates were clonal, with some evidence suggesting that the infecting strain was present in the patient's intestine at the time of admission, ruling out hospital acquisition. The use of WGS analysis is crucial to detect alternative sources of P. aeruginosa to develop new preventive measures against these serious infections.

Published
2024
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47. Enhancing audio quality for expressive Neural Text-to-Speech

Author

Ezzerg, Abdelhamid, Gabrys, Adam, Putrycz, Bartosz, Korzekwa, Daniel, Saez-Trigueros, Daniel, McHardy, David, Pokora, Kamil, Lachowicz, Jakub, Lorenzo-Trueba, Jaime, and Klimkov, Viacheslav

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Artificial Intelligence
Abstract

Artificial speech synthesis has made a great leap in terms of naturalness as recent Text-to-Speech (TTS) systems are capable of producing speech with similar quality to human recordings. However, not all speaking styles are easy to model: highly expressive voices are still challenging even to recent TTS architectures since there seems to be a trade-off between expressiveness in a generated audio and its signal quality. In this paper, we present a set of techniques that can be leveraged to enhance the signal quality of a highly-expressive voice without the use of additional data. The proposed techniques include: tuning the autoregressive loop's granularity during training; using Generative Adversarial Networks in acoustic modelling; and the use of Variational Auto-Encoders in both the acoustic model and the neural vocoder. We show that, when combined, these techniques greatly closed the gap in perceived naturalness between the baseline system and recordings by 39% in terms of MUSHRA scores for an expressive celebrity voice., Comment: 6 pages, 4 figures, 2 tables, SSW 2021

Published
2021

48. Design of a system for controlling a levitating sphere in superfluid $^3$He at extremely low temperatures

Author

Arrayás, M., Trueba, José L., Uriarte, Carlos, and Zmeev, Dmitry E.

Subjects
Condensed Matter - Superconductivity
Abstract

We present a new mechanical probe to study the properties of superfluid $^3$He at microkelvin temperatures down to 100$\mu$K. The setup consists of a set of coils for levitating a superconducting sphere and controlling its motion in a wide variety of regimes. In particular, the realisation of motion of a levitating body at a uniform velocity presents both an experimental challenge and a promising direction into the study of the edge states in topological superfluid $^3$He-B. We include the theoretical study of the device stability and simulations to illustrate the capabilities of the control system.

Published
2021
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49. Voicy: Zero-Shot Non-Parallel Voice Conversion in Noisy Reverberant Environments

Author

Mottini, Alejandro, Lorenzo-Trueba, Jaime, Karlapati, Sri Vishnu Kumar, and Drugman, Thomas

Subjects
Computer Science - Sound, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Voice Conversion (VC) is a technique that aims to transform the non-linguistic information of a source utterance to change the perceived identity of the speaker. While there is a rich literature on VC, most proposed methods are trained and evaluated on clean speech recordings. However, many acoustic environments are noisy and reverberant, severely restricting the applicability of popular VC methods to such scenarios. To address this limitation, we propose Voicy, a new VC framework particularly tailored for noisy speech. Our method, which is inspired by the de-noising auto-encoders framework, is comprised of four encoders (speaker, content, phonetic and acoustic-ASR) and one decoder. Importantly, Voicy is capable of performing non-parallel zero-shot VC, an important requirement for any VC system that needs to work on speakers not seen during training. We have validated our approach using a noisy reverberant version of the LibriSpeech dataset. Experimental results show that Voicy outperforms other tested VC techniques in terms of naturalness and target speaker similarity in noisy reverberant environments., Comment: Presented at the Speech Synthesis Workshops 2021 (SSW11)

Published
2021

50. A learned conditional prior for the VAE acoustic space of a TTS system

Author

Karanasou, Penny, Karlapati, Sri, Moinet, Alexis, Joly, Arnaud, Abbas, Ammar, Slangen, Simon, Trueba, Jaime Lorenzo, and Drugman, Thomas

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Machine Learning, Computer Science - Sound
Abstract

Many factors influence speech yielding different renditions of a given sentence. Generative models, such as variational autoencoders (VAEs), capture this variability and allow multiple renditions of the same sentence via sampling. The degree of prosodic variability depends heavily on the prior that is used when sampling. In this paper, we propose a novel method to compute an informative prior for the VAE latent space of a neural text-to-speech (TTS) system. By doing so, we aim to sample with more prosodic variability, while gaining controllability over the latent space's structure. By using as prior the posterior distribution of a secondary VAE, which we condition on a speaker vector, we can sample from the primary VAE taking explicitly the conditioning into account and resulting in samples from a specific region of the latent space for each condition (i.e. speaker). A formal preference test demonstrates significant preference of the proposed approach over standard Conditional VAE. We also provide visualisations of the latent space where well-separated condition-specific clusters appear, as well as ablation studies to better understand the behaviour of the system., Comment: in Proceedings of Interspeech 2021

Published
2021

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