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1. No evidence of magma ocean on Io based on Juno/JIRAM data

Author

Tosi, Federico, Mura, Alessandro, and Zambon, Francesca

Subjects
Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

A recent paper (ref. 1) used infrared images of Io acquired by the Juno/JIRAM instrument to derive a latitudinal dependence of the spectral radiance and conclude that such latitudinal dependence is consistent with a magma ocean model. We challenge their conclusions, and we draw attention to some potential issues with their analysis. In this letter, we will use three arguments to show that: (1) the (ref. 1) paper uses saturated data; (2) the M-filter of the JIRAM imager is only a weak and incomplete proxy for the total power output; and finally (3) even assuming that the radiance was correctly estimated, the latitudinal dependence of the 4.8-$\mu$m spectral radiance is not statistically significant. These facts, taken together, demonstrate that the results presented in (ref. 1) are not sufficient to confirm consistency with a magma ocean model on Io., Comment: 8 pages, 2 figures, 2 tables

Published
2024

2. Widespread occurrence of lava lakes on Io observed from Juno

Author

Mura, Alessandro, Tosi, Federico, Zambon, Francesca, Lopes, Rosaly M. C., Mouginis-Mark, Pete J., Radebaugh, Jani, Adriani, Alberto, Bolton, Scott, Rathbun, Julie, Cicchetti, Andrea, Grassi, Davide, Noschese, Raffaella, Piccioni, Giuseppe, Plainaki, Christina, Sordini, Roberto, and Sindoni, Giuseppe

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

We report recent observations of lava lakes within patera on Io made by the JIRAM imager/spectrometer on board the Juno spacecraft, taken during close observation occurred in the extended mission. At least 40 lava lakes have been identified from JIRAM observations. The majority (>50%) of paterae have elevated thermal signatures when imaged at sufficiently high spatial resolution (a few km/pixel), implying that lava lakes are ubiquitous on Io. The annular width of the spattering region around the margins, a characteristic of lava lakes, is of the order of few meters to tens of meters, the diameter of the observed lava lakes ranges from 10 to 100 km. The thickness of the crust in the center of some lava lakes is of the order of 5-10 m; we estimate that this crust is a few years old. Also, the bulk of the thermal emission comes from the much larger crust and not from the smaller exposed lava, so the total power output cannot be calculated from the 5-um radiance alone. Eight of the proposed lava lakes have never been reported previously as active hotspots.

Published
2024

3. Quantum Delocalization of a Levitated Nanoparticle

Author

Rossi, Massimiliano, Militaru, Andrei, Zambon, Nicola Carlon, Riera-Campeny, Andreu, Romero-Isart, Oriol, Frimmer, Martin, and Novotny, Lukas

Subjects
Quantum Physics, Physics - Optics
Abstract

Every massive particle behaves like a wave, according to quantum physics. Yet, this characteristic wave nature has only been observed in double-slit experiments with microscopic systems, such as atoms and molecules. The key aspect is that the wavefunction describing the motion of these systems extends coherently over a distance comparable to the slit separation, much larger than the size of the system itself. Preparing these states of more massive and complex objects remains an outstanding challenge. While the motion of solid-state oscillators can now be controlled at the level of single quanta, their coherence length remains comparable to the zero-point motion, limited to subatomic distances. Here, we prepare a delocalized state of a levitating solid-state nanosphere with coherence length exceeding the zero-point motion. We first cool its motion to the ground state. Then, by modulating the stiffness of the confinement potential, we achieve more than a threefold increment of the initial coherence length with minimal added noise. Optical levitation gives us the necessary control over the confinement that other mechanical platforms lack. Our work is a stepping stone towards the generation of delocalization scales comparable to the object size, a crucial regime for macroscopic quantum experiments, and towards quantum-enhanced force sensing with levitated particles.

Published
2024

4. Learning Latent Graph Structures and their Uncertainty

Author

Manenti, Alessandro, Zambon, Daniele, and Alippi, Cesare

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

Within a prediction task, Graph Neural Networks (GNNs) use relational information as an inductive bias to enhance the model's accuracy. As task-relevant relations might be unknown, graph structure learning approaches have been proposed to learn them while solving the downstream prediction task. In this paper, we demonstrate that minimization of a point-prediction loss function, e.g., the mean absolute error, does not guarantee proper learning of the latent relational information and its associated uncertainty. Conversely, we prove that a suitable loss function on the stochastic model outputs simultaneously grants (i) the unknown adjacency matrix latent distribution and (ii) optimal performance on the prediction task. Finally, we propose a sampling-based method that solves this joint learning task. Empirical results validate our theoretical claims and demonstrate the effectiveness of the proposed approach.

Published
2024

5. Temporal Graph ODEs for Irregularly-Sampled Time Series

Author

Gravina, Alessio, Zambon, Daniele, Bacciu, Davide, and Alippi, Cesare

Subjects
Computer Science - Machine Learning
Abstract

Modern graph representation learning works mostly under the assumption of dealing with regularly sampled temporal graph snapshots, which is far from realistic, e.g., social networks and physical systems are characterized by continuous dynamics and sporadic observations. To address this limitation, we introduce the Temporal Graph Ordinary Differential Equation (TG-ODE) framework, which learns both the temporal and spatial dynamics from graph streams where the intervals between observations are not regularly spaced. We empirically validate the proposed approach on several graph benchmarks, showing that TG-ODE can achieve state-of-the-art performance in irregular graph stream tasks., Comment: Preprint. Accepted at IJCAI 2024

Published
2024
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7. European Society of Intensive Care Medicine guidelines on end of life and palliative care in the intensive care unit

Author

Kesecioglu, Jozef, Rusinova, Katerina, Alampi, Daniela, Arabi, Yaseen M., Benbenishty, Julie, Benoit, Dominique, Boulanger, Carole, Cecconi, Maurizio, Cox, Christopher, van Dam, Marjel, van Dijk, Diederik, Downar, James, Efstathiou, Nikolas, Endacott, Ruth, Galazzi, Alessandro, van Gelder, Fiona, Gerritsen, Rik T., Girbes, Armand, Hawyrluck, Laura, Herridge, Margaret, Hudec, Jan, Kentish-Barnes, Nancy, Kerckhoffs, Monika, Latour, Jos M., Malaska, Jan, Marra, Annachiara, Meddick-Dyson, Stephanie, Mentzelopoulos, Spyridon, Mer, Mervyn, Metaxa, Victoria, Michalsen, Andrej, Mishra, Rajesh, Mistraletti, Giovanni, van Mol, Margo, Moreno, Rui, Nelson, Judith, Suñer, Andrea Ortiz, Pattison, Natalie, Prokopova, Tereza, Puntillo, Kathleen, Puxty, Kathryn, Qahtani, Samah Al, Radbruch, Lukas, Rodriguez-Ruiz, Emilio, Sabar, Ron, Schaller, Stefan J., Siddiqui, Shahla, Sprung, Charles L., Umbrello, Michele, Vergano, Marco, Zambon, Massimo, Zegers, Marieke, Darmon, Michael, and Azoulay, Elie

Published
2024
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9. Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations

Author

De Felice, Giovanni, Cini, Andrea, Zambon, Daniele, Gusev, Vladimir V., and Alippi, Cesare

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Virtual sensing techniques allow for inferring signals at new unmonitored locations by exploiting spatio-temporal measurements coming from physical sensors at different locations. However, as the sensor coverage becomes sparse due to costs or other constraints, physical proximity cannot be used to support interpolation. In this paper, we overcome this challenge by leveraging dependencies between the target variable and a set of correlated variables (covariates) that can frequently be associated with each location of interest. From this viewpoint, covariates provide partial observability, and the problem consists of inferring values for unobserved channels by exploiting observations at other locations to learn how such variables can correlate. We introduce a novel graph-based methodology to exploit such relationships and design a graph deep learning architecture, named GgNet, implementing the framework. The proposed approach relies on propagating information over a nested graph structure that is used to learn dependencies between variables as well as locations. GgNet is extensively evaluated under different virtual sensing scenarios, demonstrating higher reconstruction accuracy compared to the state-of-the-art., Comment: Accepted at ICLR 2024

Published
2024

10. A Tale of Two Industroyers: It was the Season of Darkness

Author

Salazar, Luis, Castro, Sebastián R, Lozano, Juan, Koneru, Keerthi, Zambon, Emmanuele, Huang, Bing, Baldick, Ross, Krotofil, Marina, Rojas, Alonso, and Cardenas, Alvaro A

Subjects
Information and Computing Sciences, Cybersecurity and Privacy
Abstract

In this paper, we study two pieces of malware that attempted to create blackouts in Ukraine. In particular, we design and develop a new sandbox that emulates different networks, devices, and other characteristics so that we can execute malware targeting substation equipment and understand in detail the specific sequence of actions the attackers could perform on substation equipment. We also study the effects that future similar malware can have. Our findings include new malware behavior not previously documented (such as the detailed algorithm for the MMS protocol payload) and an illustration of how attacking different targets will produce different effects.

Published
2024

12. Predicting mortality of cancer patients using artificial intelligence, patient data and blood tests

Author

Martins, Tiago D., Maciel-Filho, Rubens, Montalvão, Silmara A. L., Gois, Gabriele S. S., Al Bannoud, Mohamad, Ottaiano, Gabriel Y., Anhaia, Thaizy R. A., Almeida, Millene E. A., Ferreira, Monique R. M., Martinelli, Beatriz M., Fernandes, Maria C. G. L., Huber, Stephany C., Ribeiro, Daniel, Teixeira, Júlio C., Carvalheira, José B. C., Lima, Carmen S. P., Andreollo, Nelson A., Etchebehere, Maurício, Zambon, Lair, Ferreira, Ubirajara, Tincani, Alfio J., Martins, Antônio S., Coy, Cláudio S. R., Seabra, José C. T., Mussi, Ricardo K., Tedeschi, Helder, and Anninchino-Bizzacchi, Joyce M.

Published
2024
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17. Graph Deep Learning for Time Series Forecasting

Author

Cini, Andrea, Marisca, Ivan, Zambon, Daniele, and Alippi, Cesare

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Graph-based deep learning methods have become popular tools to process collections of correlated time series. Differently from traditional multivariate forecasting methods, neural graph-based predictors take advantage of pairwise relationships by conditioning forecasts on a (possibly dynamic) graph spanning the time series collection. The conditioning can take the form of an architectural inductive bias on the neural forecasting architecture, resulting in a family of deep learning models called spatiotemporal graph neural networks. Such relational inductive biases enable the training of global forecasting models on large time-series collections, while at the same time localizing predictions w.r.t. each element in the set (i.e., graph nodes) by accounting for local correlations among them (i.e., graph edges). Indeed, recent theoretical and practical advances in graph neural networks and deep learning for time series forecasting make the adoption of such processing frameworks appealing and timely. However, most of the studies in the literature focus on proposing variations of existing neural architectures by taking advantage of modern deep learning practices, while foundational and methodological aspects have not been subject to systematic investigation. To fill the gap, this paper aims to introduce a comprehensive methodological framework that formalizes the forecasting problem and provides design principles for graph-based predictive models and methods to assess their performance. At the same time, together with an overview of the field, we provide design guidelines, recommendations, and best practices, as well as an in-depth discussion of open challenges and future research directions.

Published
2023

22. Hot rings on Io observed by Juno/JIRAM

Author

Mura, Alessandro, Tosi, Federico, Zambon, Francesca, Lopes, Rosaly M. C., Mouginis-Mark, Peter J., Becker, Heidi, Filacchione, Gianrico, Migliorini, Alessandra, Hansen, Candice. J., Adriani, Alberto, Altieri, Francesca, Bolton, Scott, Cicchetti, Andrea, Di Mico, Elisa, Grassi, Davide, Noschese, Raffaella, Moirano, Alessandro, Pettine, Madeline, Piccioni, Giuseppe, Plainaki, Christina, Rathbun, Julie, Sordini, Roberto, and Sindoni, Giuseppe

Published
2024
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25. A collaborative effort across Africa to investigate risk factors and outcomes of premature acute coronary syndrome: Protocol for the EAS Lipid Registry of Africa (LIPRA)

Author

Ashraf Reda, Alexander R.M. Lyons, Alberto Zambon, Ahmed Bendary, Mutaz Al-Khnifsawi, Habib Gamra, David Marais, Okechukwu S. Ogah, Tigist Seleshi, Ahmed A.A. Suliman, Julius C. Mwita, Albertino Damasceno, Anastase Dzudie, Atef Elbahry, Elsayed Farag, Chala Fekadu, Lilian Mbau, Mohammed Mujahed, Rosemary P. Minja, Bernard Samia, Mahmoud Sani, Lambert T. Appiah, and Alexandros Tselepis

Subjects
Acute coronary syndrome, Premature acute coronary syndrome, Cardiovascular disease risk, Coronary artery disease, EAS LIPRA, NSTEMI, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Data on acute coronary syndrome (ACS) is lacking in Africa where cases of premature ACS seem to be on the rise. Africa would benefit from an epidemiological assessment of premature ACS to determine its risk factors and management in this demographic to inform guidelines and practice. The European Atherosclerosis Society recognised this urgency and formed a growing network across 11 African countries to create the Lipid Registry of Africa (EAS-LIPRA). This article is based on the EAS-LIPRA protocol and presents the aims, concept and methodological considerations, and the operations and collaborative governance structure of this project. EAS-LIPRA aims to report risk factors and outcomes of premature ACS in Africa to further understand its prevalence and management via collating and pooling multinational prospective data on premature ACS across multiple sites in Africa into a standardised registry. Data will be stratified into subgroups based on country-level income as defined by the World Bank, and within country residence of urban versus rural areas. Valid statistical procedures will be employed to compare and observe trends in the pooled data based on demographics, clinical and laboratory variables, and disparities in its management. Being the first multinational lipid registry in Africa, it is envisaged that the network will expand to other African countries and sites yet to participate, facilitate other epidemiological studies in preventive cardiology, and set a precedent for other developing countries and regions.

Published
2024
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26. Rumen-protected methionine supplementation during the transition period under artificially induced heat stress: Effects on cow-calf performance

Author

B.D. Davidson, A.A. Zambon, A.R. Guadagnin, A. Hoppmann, G.A. Larsen, D.N. Sherlock, D. Luchini, S.I. Arriola Apelo, and J. Laporta

Subjects
hyperthermia, heat blanket, methionine, transition, Dairy processing. Dairy products, SF250.5-275, Dairying, SF221-250
Abstract

ABSTRACT: Dairy cows experiencing heat stress (HS) during the precalving portion of the transition period give birth to smaller calves and produce less milk and milk protein. Supplementation of rumen-protected methionine (RPM) has been shown to modulate protein, energy, and placenta metabolism, making it a potential candidate to ameliorate HS effects. We investigated the effects of supplementing RPM to transition cows under HS induced by electric heat blanket (EHB) on cow-calf performance. Six weeks before expected calving, 53 Holstein cows were housed in a tiestall barn and fed a control diet (CON, 2.2% Met of MP) or a CON diet supplemented with SmartamineM (MET, 2.6% Met of MP, Adisseo Inc., France). Four weeks precalving, all MET and half CON cows were fitted with an EHB. The other half of the CON cows were considered thermoneutral (TN), resulting in 3 treatments: CONTN (n = 19), CONHS (n = 17), and METHS (n = 17). Respiratory rate (RR), skin temperature (ST), and rectal temperature (RT) were measured thrice weekly and core body temperatures recorded biweekly. Postcalving BW and BCS were recorded weekly, and DMI was calculated and averaged weekly. Milk yield was recorded daily and milk components were analyzed every third DIM. Biweekly AA and weekly nonesterified fatty acids (NEFA), BHB, insulin, and glucose were measured from plasma. Calf birth weight and 24 h growth, thermoregulation, and hematology profile were measured and apparent efficiency of absorption (AEA) of immunoglobulins was calculated. Data were analyzed using the MIXED procedure of SAS with 2 preplanned orthogonal contrasts: CONTN versus the average of CONHS and METHS (C1) and CONHS versus METHS (C2). Relative to TN, EHB cows had increased RT during the postcalving weeks and increased RR and ST during the entire transition period. Body weight, BCS, DMI, and milk yield were not affected by the EHB or RPM. However, protein percentage and SNF were lower in CONHS, relative to METHS cows. At calving, METHS dams had higher glucose concentrations, relative to CONHS, and during the postcalving weeks, the EHB cows had lower NEFA concentrations than TN cows. Calf birthweight and AEA were reduced by HS, whereas RR was increased by HS. Calf withers height tended to be shorter and RT were lower in CONHS, compared with METHS heifers. Overall, RPM supplementation to transition cows reverts the negative effect of HS on blood glucose concentration at calving and milk protein percentage in the dams and increases wither height while decreasing RT in the calf.

Published
2024
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27. JIRAM Observations of Volcanic Flux on Io: Distribution and Comparison to Tidal Heat Flow Models

Author

Pettine, M., Imbeah, S., Rathbun, J., Hayes, A., Lopes-Gautier, R., Mura, A., Tosi, F., Zambon, F., and Bertolino, S.

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

Juno has allowed clear, high-resolution imaging of Io's polar volcanoes using the Jovian Infrared Auroral Mapper (JIRAM) instrument. We have used data from JIRAM's M-band (4.78 um) imager from eleven Juno orbits to construct a global map of volcanic flux. This map provides short-term insight into the spatial distribution of volcanoes and the ways in which high- and low-latitude volcanoes differ. Using spherical harmonic analysis, we quantitatively compare our volcanic flux map to the surface heat flow distribution expected from models of Io's tidal heat deposition (summarized in de Kleer et al. 2019). Our observations confirm previously detected systems of bright volcanoes at high latitudes. Our study finds that both poles are comparably active and that the observed flux distribution is inconsistent with an asthenospheric heating model, although the south pole is viewed too infrequently to establish reliable trends., Comment: 11 pages, 3 figures

Published
2023
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28. A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection

Author

Jin, Ming, Koh, Huan Yee, Wen, Qingsong, Zambon, Daniele, Alippi, Cesare, Webb, Geoffrey I., King, Irwin, and Pan, Shirui

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series analytics is therefore crucial to unlocking the wealth of information implicit in available data. With the recent advancements in graph neural networks (GNNs), there has been a surge in GNN-based approaches for time series analysis. These approaches can explicitly model inter-temporal and inter-variable relationships, which traditional and other deep neural network-based methods struggle to do. In this survey, we provide a comprehensive review of graph neural networks for time series analysis (GNN4TS), encompassing four fundamental dimensions: forecasting, classification, anomaly detection, and imputation. Our aim is to guide designers and practitioners to understand, build applications, and advance research of GNN4TS. At first, we provide a comprehensive task-oriented taxonomy of GNN4TS. Then, we present and discuss representative research works and introduce mainstream applications of GNN4TS. A comprehensive discussion of potential future research directions completes the survey. This survey, for the first time, brings together a vast array of knowledge on GNN-based time series research, highlighting foundations, practical applications, and opportunities of graph neural networks for time series analysis., Comment: 37 pages, 6 figures, 7 tables; Project page: https://github.com/KimMeen/Awesome-GNN4TS

Published
2023

32. Adding integrable defects to the Boussinesq equation

Author

Corrigan, E. and Zambon, C.

Subjects
Nonlinear Sciences - Exactly Solvable and Integrable Systems, High Energy Physics - Theory
Abstract

The purpose of this paper is to extend the store of models able to support integrable defects by investigating the two-dimensional Boussinesq nonlinear wave equation. As has been previously noted in many examples, insisting that a defect contributes to energy and momentum to ensure their conservation, despite the presence of discontinuities and the explicit breaking of translation invariance, leads to sewing conditions relating the two fields and their derivatives on either side of the defect. The manner in which several types of soliton solutions to the Boussinesq equation are affected by the defect is explored and reveals new effects that have not been observed in other integrable systems, such as the possibility of a soliton reflecting from a defect or of a defect decaying into one or two solitons., Comment: 28 pages, 9 figures

Published
2023

33. Graded geometry and generalized reduction

Author

Bursztyn, Henrique, Cattaneo, Alberto S., Mehta, Rajan Amit, and Zambon, Marco

Subjects
Mathematics - Symplectic Geometry, High Energy Physics - Theory, Mathematics - Differential Geometry
Abstract

We present general reduction procedures for Courant, Dirac and generalized complex structures, in particular when a group of symmetries is acting. We do so by taking the graded symplectic viewpoint on Courant algebroids and carrying out graded symplectic reduction, both in the coisotropic and hamiltonian settings. Specializing the latter to the exact case, we recover in a systematic way the reduction schemes of Bursztyn-Cavalcanti-Gualtieri., Comment: 80 pages. v2: Added Lemma 7.1. Added Example 6.15 and consequences thereof (Examples 7.6, 7.7, 7.12, 8.20, 8.21, 8.22)

Published
2023

34. Deformations of Symplectic Foliations: algebraic aspects

Author

Geudens, Stephane, Tortorella, Alfonso G., and Zambon, Marco

Subjects
Mathematics - Symplectic Geometry, Mathematics - Quantum Algebra
Abstract

In the companion paper arXiv:2110.05298, we developed the deformation theory of symplectic foliations, focusing on geometric aspects. Here, we address some algebraic questions that arose naturally. We show that the $L_{\infty}$-algebra constructed there is independent of the choices made, and we prove that the gauge equivalence of Maurer-Cartan elements corresponds to the equivalence by isotopies of symplectic foliations., Comment: 26 pages

Published
2023

35. Stability of fixed points of Dirac structures

Author

Singh, Karandeep Jandu and Zambon, Marco

Subjects
Mathematics - Symplectic Geometry, Mathematics - Quantum Algebra, primary 17B70, 53D17, secondary 8H15
Abstract

Given an $L_{\infty}$-algebra $V$ and an $L_{\infty}$-subalgebra $W$, we give sufficient conditions for all small Maurer-Cartan elements of $V$ to be equivalent to Maurer-Cartan elements lying in $W$. As an application, we obtain a stability criterion for fixed points of a Dirac structure (for instance a twisted Poisson structure), i.e. points where the corresponding leaf is zero-dimensional. The criterion guarantees that any nearby Dirac structure also has a fixed point., Comment: Final version, accepted for publication. 22 pages

Published
2023
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36. FÁBRICA DE IDEIAS E INOVAÇÃO

Author

LINO LIMA ZAMBON DE MENDONÇA, BRUNA SUASSUNA, and Verner Monteiro

Subjects
concurso de projeto, arquitetura em aço, processo de projeto, Architecture, NA1-9428, Urban groups. The city. Urban sociology, HT101-395
Abstract

A construção em aço ainda é, em grande medida, um mito em algumas escolas de arquitetura. A formação brasileira, de modo geral, ainda é fortemente influenciada pelo modernismo, que tem no concreto armado a representação de material e sistema estrutural incontestáveis. Contudo, a contemporaneidade tenta romper as barreiras e difundir o uso de materiais alternativos. Uma das alternativas principais é o aço, que lança oportunidade de soluções mais diversas e ousadas, uma vez que possibilita uso de balanços, atirantamentos e vãos maiores. Este artigo tem como objetivo apresentar um projeto concebido em aço para o concurso do Centro Brasileiro da Construção em Aço, o CBCA, focando na apresentação do processo de projeto e da proposta as soluções arquitetônicas e estruturais utilizadas. O manuscrito mostra, ainda, os bastidores do que precisou ser preparado nas etapas da competição, revelando os principais desafios colocados à equipe de projeto.

Published
2024
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37. Delirium in nursing home residents: is there a role of antidepressants? A cross sectional study

Author

Massimiliano Fedecostante, Paolo Balietti, Simona Gabriella Di Santo, Antonella Zambon, Alessandra Marengoni, Alessandro Morandi, Alessia Beccacece, Giuseppe Bellelli, and Antonio Cherubini

Subjects
Delirium, Nursing home, 4AT, Delirium subtypes, Antidepressants, SSRIs, Geriatrics, RC952-954.6
Abstract

Abstract Background Delirium is strongly associated with poor health outcomes, yet it is frequently underdiagnosed. Limited research on delirium has been conducted in Nursing Homes (NHs). Our aim is to assess delirium prevalence and its associated factors, in particular pharmacological prescription, in this care setting. Methods Data from the Italian “Delirium Day” 2016 Edition, a national multicenter point-prevalence study on patients aged 65 and older were analyzed to examine the associations between the prevalence of delirium and its subtypes with demographics and information about medical history and pharmacological treatment. Delirium was assessed using the Assessment test for delirium and cognitive impairment (4AT). Motor subtype was evaluated using the Delirium Motor Subtype Scale (DMSS). Results 955 residents, from 32 Italian NHs with a mean age of 84.72 ± 7.78 years were included. According to the 4AT, delirium was present in 260 (27.2%) NHs residents, mainly hyperactive (35.4%) or mixed subtypes (20.7%). Antidepressant treatment with selective serotonin reuptake inhibitors (SSRIs) was associated with lower delirium prevalence in univariate and multivariate analyses. Conclusions The high prevalence of delirium in NHs highlights the need to systematically assess its occurrence in this care settings. The inverse association between SSRIs and delirium might imply a possible preventive role of this class of therapeutic agents against delirium in NHs, yet further studies are warranted to ascertain any causal relationship between SSRIs intake and reduced delirium incidence.

Published
2024
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38. Lessons from PROMINENT and prospects for pemafibrate

Author

Jean-Charles Fruchart, Jamila Fruchart-Najib, Shizuya Yamashita, Peter Libby, Koutaro Yokote, Tatsuhiko Kodama, Yohei Tomita, Paul M. Ridker, Michel P. Hermans, and Alberto Zambon

Subjects
PROMINENT trial, Pemafibrate, Type 2 diabetes mellitus, Diabetic retinopathy, Peripheral artery disease, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Abstract The neutral result of the PROMINENT trial has led to questions about the future for pemafibrate. This commentary discusses possible reasons for the lack of benefit observed in the trial. There were, however, indicators suggesting therapeutic potential in microvascular ischaemic complications associated with peripheral artery disease, with subsequent analysis showing reduction in the incidence of lower extremity ischaemic ulceration or gangrene. Reassurance about the safety of pemafibrate, together with emerging data from PROMINENT and experimental studies, also suggest benefit with pemafibrate in non-alcoholic fatty liver disease (alternatively referred to as metabolic dysfunction-associated steatotic liver disease) and microangiopathy associated with diabetes, which merit further study.

Published
2024
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39. Post-intensive care syndrome screening: a French multicentre survey

Author

Maïté Agbakou, Margot Combet, Maëlle Martin, Gauthier Blonz, Luc Desmedt, Amélie Seguin, Jérémie Lemarié, Olivier Zambon, Jean Reignier, Jean-Baptiste Lascarrou, Stephan Ehrmann, and Emmanuel Canet

Subjects
Intensive care unit, Survey, France, Post-intensive care syndrome, Disability, Screening, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Abstract Background Post-intensive care syndrome (PICS), defined as physical, cognitive, and mental-health symptoms persisting long after intensive-care-unit (ICU) discharge, is increasingly recognised as a healthcare priority. Data on screening for PICS are sparse. Our objective here was to describe post-ICU screening in France, with special attention to visit availability and evaluations done during visits. Methods We conducted an online multicentre survey by emailing an anonymous 43-item questionnaire to French ICUs. For each ICU, a single survey was sent to either the head or the intensivist in charge of follow-up visits. Results Of 252 ICUs invited to participate, 161 (63.9%) returned the completed survey. Among them, 46 (28.6%) offered follow-up visits. Usually, a single visit led by an intensivist was scheduled 3 to 6 months after ICU discharge. Approximately 50 patients/year/ICU, that is, about 5% of admitted patients, attended post-ICU visits. The main criteria used to select patients for follow-up were ICU stay and/or invasive mechanical ventilation duration longer than 48 h, cardiac arrest, septic shock, and acute respiratory distress syndrome. Among ICUs offering visits, 80% used validated instruments to screen for PICS. Of the 115 ICUs not offering follow-up, 50 (43.5%) indicated an intention to start follow-up within the next year. The main barriers to offering follow-up were lack of available staff and equipment or not viewing PICS screening as a priority. Half the ICUs offering visits worked with an established network of post-ICU care professionals, and another 17% were setting up such a network. Obstacles to network creation were lack of interest among healthcare professionals and lack of specific training in PICS. Conclusion Only a small minority of ICU survivors received follow-up designed to detect PICS. Less than a third of ICUs offered follow-up visits but nearly another third planned to set up such visits within the next year. Recommendations issued by French health authorities in 2023 can be expected to improve the availability and standardisation of post-ICU follow-up.

Published
2024
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40. Effect of the welding technique and post-welding heat treatments on the microstructure and mechanical properties of a high silicon nanostructured carbide-free bainitic steel

Author

Mattia Franceschi, Edoardo Bregolin, Alvise Miotti-Bettanini, Luca Pasqualini, Simone Campagnolo, Andrea Zambon, Luca Pezzato, and Manuele Dabalà

Subjects
Steel, Bainite, Welding, Mechanical properties, Mining engineering. Metallurgy, TN1-997
Abstract

Recently carbide free bainitic steels, with microstructure consisting in nanoscaled bainitic ferrite plates and high carbon-enriched austenite, have been developed. These steels have found commercial use in manufacturing engineering components, nevertheless, their high carbon concentration poses a limitation as they cannot be welded, restricting their potential applications, therefore the actual research has shifted to the investigation to medium carbon steels. In this work, Butt weld – V groove weldment have been realized with a novel medium carbon high silicon carbide-free bainitic steel by means GMAW and GTAW. Optical microscopy, scanning and transmission electron microscopy and X-ray diffraction were used to characterize the microstructures of both the fusion and heat affected zone. Dilatometry was utilized to study the phase transformations during post-welding heat treatment. Tensile and micro-hardness tests were carried out to evaluate the mechanical properties in the as-weld state after post-welding heat treatment. The analysis shows the possibility to obtain high strength weldments with high integrity and high strength (>1 GPa) coupled with reasonable ductility and the absence of cold or hot cracking phenomena.

Published
2024
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41. Characterization of the Surfaces and Near-Surface Atmospheres of Ganymede, Europa and Callisto by JUICE

Author

Tosi, Federico, Roatsch, Thomas, Galli, André, Hauber, Ernst, Lucchetti, Alice, Molyneux, Philippa, Stephan, Katrin, Achilleos, Nicholas, Bovolo, Francesca, Carter, John, Cavalié, Thibault, Cimò, Giuseppe, D’Aversa, Emiliano, Gwinner, Klaus, Hartogh, Paul, Huybrighs, Hans, Langevin, Yves, Lellouch, Emmanuel, Migliorini, Alessandra, Palumbo, Pasquale, Piccioni, Giuseppe, Plaut, Jeffrey J., Postberg, Frank, Poulet, François, Retherford, Kurt, Rezac, Ladislav, Roth, Lorenz, Solomonidou, Anezina, Tobie, Gabriel, Tortora, Paolo, Tubiana, Cecilia, Wagner, Roland, Wirström, Eva, Wurz, Peter, Zambon, Francesca, Zannoni, Marco, Barabash, Stas, Bruzzone, Lorenzo, Dougherty, Michele, Gladstone, Randy, Gurvits, Leonid I., Hussmann, Hauke, Iess, Luciano, Wahlund, Jan-Erik, Witasse, Olivier, Vallat, Claire, and Lorente, Rosario

Published
2024
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42. Graph Kalman Filters

Author

Alippi, Cesare and Zambon, Daniele

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

The well-known Kalman filters model dynamical systems by relying on state-space representations with the next state updated, and its uncertainty controlled, by fresh information associated with newly observed system outputs. This paper generalizes, for the first time in the literature, Kalman and extended Kalman filters to discrete-time settings where inputs, states, and outputs are represented as attributed graphs whose topology and attributes can change with time. The setup allows us to adapt the framework to cases where the output is a vector or a scalar too (node/graph level tasks). Within the proposed theoretical framework, the unknown state-transition and the readout functions are learned end-to-end along with the downstream prediction task., Comment: Added empirical validation

Published
2023

43. Taming Local Effects in Graph-based Spatiotemporal Forecasting

Author

Cini, Andrea, Marisca, Ivan, Zambon, Daniele, and Alippi, Cesare

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Spatiotemporal graph neural networks have shown to be effective in time series forecasting applications, achieving better performance than standard univariate predictors in several settings. These architectures take advantage of a graph structure and relational inductive biases to learn a single (global) inductive model to predict any number of the input time series, each associated with a graph node. Despite the gain achieved in computational and data efficiency w.r.t. fitting a set of local models, relying on a single global model can be a limitation whenever some of the time series are generated by a different spatiotemporal stochastic process. The main objective of this paper is to understand the interplay between globality and locality in graph-based spatiotemporal forecasting, while contextually proposing a methodological framework to rationalize the practice of including trainable node embeddings in such architectures. We ascribe to trainable node embeddings the role of amortizing the learning of specialized components. Moreover, embeddings allow for 1) effectively combining the advantages of shared message-passing layers with node-specific parameters and 2) efficiently transferring the learned model to new node sets. Supported by strong empirical evidence, we provide insights and guidelines for specializing graph-based models to the dynamics of each time series and show how this aspect plays a crucial role in obtaining accurate predictions., Comment: Accepted at NeurIPS 2023

Published
2023

44. How did previously obese children and adolescents behave during the SARS-CoV-2 pandemic in relation to weight gain?

Author

Mirella Menaque da Paz, Fábio de Freitas, Mariana Renata Zago, Mariana Porto Zambon, and Maria Ângela Reis de Góes Monteiro Antônio

Subjects
Children, Adolescents, Pediatric obesity, Weight gain, Pandemic, Pediatrics, RJ1-570
Abstract

ABSTRACT Objective: The objective of this study was to analyze the implications of social contingency measures and interruption of outpatient follow-up on weight gain in children and adolescents with a previous diagnosis of obesity. Methods: This is an observational study with data from electronic medical records of children and adolescents followed up at a specialized outpatient clinic from 2019 to 2023. Weight gain, height, BMI variation, BMI z-score, laboratory tests, and associated comorbidities were analyzed. The data were computed and analyzed using the Statistical Package for the Social Sciences (SPSS), and the results were considered statistically significant when p

Published
2024
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45. Potential for material valorization of composites (glass fiber in polyester resin) in concrete: performance evaluation on mortar

Author

Agnès Zambon and Mylène Deleglise-Lagardere

Subjects
material valorization, glass fiber, polyester resin, composite, concrete, resource preservation, Technology
Abstract

IntroductionGlass fibers with polyester resin structural composites are highly sought after in many sectors such as transportation industries, thanks to their low density and fairly good mechanical properties. However, their end-of-life management is not yet satisfactory. Composites mostly end in energy recovery in the best-case scenario or, worse, in landfills. Transformation into shreds and powders for reuse as a new source of raw material for the construction sector (concrete) is an economically and environmentally attractive recovery solution. The present study investigates the development of a concrete filled with glass/polyester composite shreds.MethodsTo this end, rheological (cone spread) and physico-mechanical (density and mechanical strength in flexion and compression) characterization tests were carried out. Several mix designs were tested in order to understand the impact of introducing composite shreds as a substitute for sand. Composite shreds were introduced in the following ratios by volume: 0, 1, 1.5, 2, 2.5, 3, and 7% with water and cement ratio equal to 0.5, 0.6, and 0.7.Results and discussionThe results obtained indicate that workability decreases with the substitution of sand by shreds. For a substitution of sand by shreds of 2%, it is relatively small, and the pouring of the mortar is still feasible. The decrease can be attributed to the water absorption of the composite shreds. Concerning mechanical results, for formulations with a substitution percentage of composite shreds lower than 3%, the mechanical strength (both compression test and flexure test) is slightly higher than that of the reference sample. The increase in compressive strength that can be observed is at its maximum, equal to 10%, compared to that of the reference sample. These results are in line with density results, which are also slightly higher than that of the reference sample. This effect can be attributed to water absorption of composite shreds and the filling effect of the powders. For a percentage of substitution equal to 7%, the mechanical strength is lower than that of the reference sample (30% decrease), with a compressive strength equal to 33 MPa (47 MPa for the reference sample). For this percentage of substitution equal to 7%, a decrease in density is also observed (6% decrease) and can be explained by the porosity created by the incorporation of the composite shreds into the mortar.

Published
2024
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46. Long Covid: a global health issue – a prospective, cohort study set in four continents

Author

Synne Jenum, Renaud Tamisier, Clark D Russell, Rachel Evans, Piero Valentini, Sylvain Diamantis, Dominique Deplanque, Jordi Rello, Agnes Meybeck, Maxime Hentzien, Clotilde Allavena, André Cabié, Firouzé Bani-Sadr, Patrick Rossignol, Lionel Piroth, Mathieu Blot, Marie-Pierre Debray, François Angoulvant, Marc Leone, Ewen M Harrison, Maria Zambon, Michael Edelstein, Florentia Kaguelidou, Marc Lambert, Olivier Lairez, Tom Solomon, Carrol Gamble, Laura Marsh, Christiana Kartsonaki, Natalie Wright, Behzad Nadjm, Srinivas Murthy, Gail Carson, Jake Dunning, Laura Merson, Peter Horby, Timothy M Uyeki, Piero Olliaro, Guillermo Maestro de la Calle, Stephen R Knight, Thomas M Drake, Marlene Murris, Aurore Bousquet, Kenneth A McLean, Hugues Cordel, Marc Fabre, Laurence Bouillet, Katrina Hann, Xavier Duval, James Lee, Christian Rabaud, Paul Klenerman, Jean-Christophe Lucet, Jean-François Timsit, Jennifer Lee, David J Lowe, Nicolas Terzi, Saad Nseir, Gwenhaël Colin, Steve Webb, Kalynn Kennon, Caroline Mudara, Diana Hernández, Yazdan Yazdanpanah, Jean-François Payen, Samreen Ijaz, Joanne McPeake, Meera Chand, Catherine A Shaw, Cameron J Fairfield, Bruno Levy, Eric D'ortenzio, Pierre Delobel, Tiphaine Goulenok, Bronner P Gonçalves, Arnaud Scherpereel, Danilo Buonsenso, Mark G Pritchard, Susanne Dudman, Adrien Auvet, Caterina Caminiti, Debby Bogaert, Elisabeth Botelho-Nevers, Amandine Gagneux-Brunon, Merce Jourdain, Sue Smith, Jia Wei, Antoine Khalil, Clément Le Bihan, Nathalie Pansu, Vincent Le Moing, Victor Fomin, Christophe Fraser, Daniel Munblit, William Greenhalf, François-Xavier Lescure, Nicolas Carlier, Saye Khoo, Annemarie B Docherty, Christopher A Green, Riinu Pius, Louise Sigfrid, Sophie Halpin, Clare Jackson, Antonia Ho, Malcolm G Semple, Andrew Dagens, Carlo Palmieri, Lance Turtle, Zeno Bisoffi, Thomas Flament, Julie Mankikian, Romain Basmaci, Peter Openshaw, Rob Fowler, Tom Fletcher, Adrien Lemaignen, Pierre Tattevin, Christelle Delmas, Hélène Espérou, Claire Lévy-Marchal, Olivier Picone, Jeanne Sibiude, Cecile Yelnik, Michelle Girvan, Piero L Olliaro, Beatrice Alex, Benjamin Bach, Wendy S Barclay, Graham S Cooke, Ana da Silva Filipe, Alexander J Mentzer, Alison M Meynert, Mahdad Noursadeghi, Shona C Moore, Massimo Palmarini, William A Paxton, Georgios Pollakis, David L Robertson, Vanessa Sancho-Shimizu, Janet T Scott, Shiranee Sriskandan, David Stuart, Charlotte Summers, Emma C Thomson, Ryan S Thwaites, Lance C W Turtle, Hayley Hardwick, Wilna Oosthuyzen, Fiona Griffiths, Jo Dalton, Egle Saviciute, Stephanie Roberts, Janet Harrison, Marie Connor, Gary Leeming, Ross Hendry, Victoria Shaw, Jade Ghosn, Lucille Blumberg, Nicolas Benech, Odile Launay, Yoan Lavie-Badie, Minh Le, Elise Artaud-Macari, Muge Cevik, Nicola Latronico, Mylène Maillet, Didier Laureillard, Ben Morton, Claire Hastie, Nicholas Sedillot, Anne-Sophie Boureau, Laurent Abel, Guillaume Martin-Blondel, Valérie Garrait, Isabelle Delacroix, Andrea Cortegiani, Jean-Benoît Arlet, Raphaël Borie, Kévin Bouiller, Vincent Langlois, Mélanie Roriz, Vincent Dubée, John H Amuasi, Madiha Hashmi, Edwin Jesudason, Jan Cato Holter, Anders Benjamin Kildal, Luis Felipe Reyes, Anna Beltrame, Sulaiman Lakoh, Stéphanie Fry, Lynsey Goodwin, Laurent Plantier, Anna Casey, Denis Malvy, Nina Jamieson, François Dubos, Jean-Sébastien Hulot, Paola Rodari, Frank Bloos, Cécile Tromeur, Paul Loubet, Marina Esposito-Farèse, France Mentré, Valérie Gaborieau, Cécile Goujard, Vincent Thibault, Adam Ali, Sadie Kelly, Fernando A Bozza, Bertrand Dussol, Marion Schneider, Marielle Buisson, Yves Levy, Carine Roy, Walter Picard, Olivier Sanchez, Nazir Lone, Antoine Kimmoun, Roberto Roncon-Albuquerque, Nathan Peiffer-Smadja, Julien Poissy, Lila Bouadma, Bruno Lina, Maude Bouscambert, Alexandre Gaymard, Gilles Peytavin, Jeremie Guedj, Claire Andrejak, Cedric Laouenan, Anissa Chair, Samira Laribi, Marie-Capucine Tellier, Sandrine Couffin-Cadiergues, Ventzislava Petrov-Sanchez, Alpha Diallo, Sarah Tubiana, Patrick Imbert, Emmanuelle Mercier, Waasila Jassat, Arsene Kpangon, Dominique Luton, Simone Piva, Sophie Mahy, Pierre-Adrien Bolze, Sarah Moore, Raphael Favory, Andrea Angheben, Andrea Rossanese, Matthew Hall, Johann Auchabie, Christophe Rapp, Vincent Peigne, Fredrik Müller, Christl A Donnelly, François Goehringer, Elodie Curlier, Catherine Chirouze, Vegard Skogen, Stéphane Jaureguiberry, Laurent Bitker, Hodane Yonis, Laurent Mandelbrot, Jérémie Pasquier, Bato Hammarström, Thushan de Silva, Polina Bugaeva, Julie Chas, Dario Sinatti, Arne Søraas, Murray Wham, Sara Clohisey, Seán Keating, Thibault Chiarabini, Agnes Sommet, Hugues Aumaître, Charlotte Charpentier, Sylvie LeGac, Sarah E McDonald, Jeanne Truong, Anne-Hélène Boivin, Mariachiara Ippolito, Ellen Pauley, Diane Descamps, Sérgio Gaião, Stéphane Lasry, Amanda Rojek, Charlotte Salmon Gandonniere, Sebastien Preau, Benoit Thill, Karine Faure, Denis Garot, Grégory Corvaisier, Elsa Nyamankolly, Merete Ellingjord-Dale, Eva Geraud, Barbara Wanjiru Citarella, Kévin Alexandre, Nathalie Allou, Séverine Ansart, Laurène Azemar, Cecile Azoulay, Delphine Bachelet, Claudine Badr, Valeria Balan, Marie Bartoli, Joaquín Baruch, Jules Bauer, Alexandra Bedossa, Husna Begum, Marine Beluze, Delphine Bergeaud, Giulia Bertoli, Simon Bessis, Sybille Bevilcaqua, Karine Bezulier, Krishna Bhavsar, Laetitia Bodenes, Isabela Bolaños, Olivier Bouchaud, Sabelline Bouchez, Camile Bouisse, Marielle Boyer-Besseyre, Axelle Braconnier, Ingrid G Bustos, Denis Butnaru, Eder Caceres, Cyril Cadoz, Valentine Campana, Pauline Caraux-Paz, Thierry Carmoi, Marie-Christine Carret, Maire-Laure Casanova, Guylaine Castor-Alexandre, François-Xavier Catherine, Minerva Cervantes-Gonzalez, Catherine Chakveatze, Jean-Marc Chapplain, Antoine Cheret, Bernard Cholley, Marie-Charlotte Chopin, Roxane Courtois, Stéphanie Cousse, Alexa Debard, Nathalie DeCastro, Romain Decours, Eve Defous, Karen Delavigne, Elisa Demonchy, Emmanuelle Denis, Mathilde Desvallées, Kévin Didier, Jean-Luc Diehl, Vincent Dinot, Fara Diop, Alphonsine Diouf, Félix Djossou, Céline Dorival, Nathalie Dournon, Murray Dryden, Alexandre Ducancelle, Paul Dunand, Brigitte Elharrar, Philippine Eloy, Isabelle Enderle, Ilka Engelmann, Vincent Enouf, Olivier Epaulard, Manuel Etienne, Isabelle Fabre, François-Xavier Ferrand, Eglantine Ferrand Devouge, Nicolas Ferriere, Céline Ficko, Erwan Fourn, Rostane Gaci, Jean-Charles Gagnard, Esteban Garcia-Gallo, Tristan Gigante, Guillermo Giordano, Valérie Gissot, Petr Glybochko, Marie Gominet, Isabelle Gorenne, Laure Goubert, Pascal Granier, Segolène Greffe, Martin Guego, Romain Guery, Anne Guillaumot, Laurent Guilleminault, Thomas Guimard, Ali Hachemi, Nadir Hadri, Rebecca Hamidfar, Lars Heggelund, Rupert Higgins, Hikombo Hitoto, Alexandre Hoctin, Isabelle Hoffmann, Ikram Houas, Margaux Isnard, Danielle Jaafar, Salma Jaafoura, Julien Jabot, Florence Jego, Cédric Joseph, Ouifiya Kafif, Sabina Kali, Younes Kerroumi, Marie Lachatre, Marie Lacoste, Marie Lagrange, Fabrice Laine, Antonio Lalueza, Marie Langelot-Richard, Delphine Lariviere, Andy Law, Laurent Lefebvre, Bénédicte Lefebvre, Benjamin Lefèvre, Jean-Daniel Lelievre, Véronique Lemee, Anthony Lemeur, Quentin Lepiller, Olivier Lesens, Mathieu Lesouhaitier, Geoffrey Liegeon, Guillaume Lingas, Sylvie Lion-Daolio, Marine Livrozet, Bouchra Loufti, Guillame Louis, Liem Luong, Moïse Machado, Gabriel Macheda, Rafael Mahieu, Thomas Maitre, Victoria Manda, Aldric Manuel, Samuel Markowicz, Martin Martinot, Mathieu Mattei, Laurence Maulin, Thierry Mazzoni, Cécile Mear-Passard, Antoine Merckx, Mayka Mergeay-Fabre, Vanina Meysonnier, Mehdi Mezidi, Isabelle Michelet, Lucia Moro, Julien Moyet, Jimmy Mullaert, Nadège Neant, Nikita Nekliudov, Anthony Nghi, Duc Nguyen, Nadia Ouamara, Rachida Ouissa, Eric Oziol, Justine Pages Maïder Pagadoy, Aurélie Papadopoulos, Bruno Pastene, Christelle Paul, Florent Peelman, Daniel Perez, Thomas Perpoint, Vincent Pestre, Ryadh Pokeerbux, Diane Ponscarme, Marie Rafiq, Blandine Rammaert, Stanislas Rebaudet, Sarah Redl, Anne-Sophie Resseguier, Matthieu Revest, Laurent Richier, Patrick Rispal, Karine Risso, Olivier Robineau, Manuel Rosa-Calatrava, Benoît Roze, Hélène Salvator, Pierre-François Sandrine, Benjamine Sarton, Eric Senneville, Albert Sotto, Sarah Stabler, Andrey Svistunov, Coralie Tardivon, François Téoulé, Olivier Terrier, Simon-Djamel Thiberville, Peter S Timashev, Noémie Tissot, Tiffany Trouillon, Christelle Tual, Noémie Vanel, Charline Vauchy, Aurélie Veislinger, Fanny Vuotto, Aurélie Wiedemann, Marion Zabbe, David Zucman, Silvio Hamacher, Ekaterina Pazukhina, Allegra Chatterjee, Kyle Gomez, Matteo Puntoni, Oksana Kruglova, Yock Ping Chow, Yash Doshi, Sara Isabel Duque Vallejo, Elsa D Ibáñez-Prada, Yuli V Fuentes, Margaret E O'Hara, Tigist Menkir, Amal Abrous, Younes Ait Tamlihat, Aliya Mohammed Alameen, Marta Alessi, Kazali Enagnon Alidjnou, Jean Baptiste Assie, Eyvind W Axelsen, John Kenneth Baillie, José Luis Bernal Sobrino, Sonja Hjellegjerde Brunvoll, Roar Bævre-Jensen, Jose Andres Calvache, Léo Chenard, Juan Luis Cruz Bermúdez, Jaime Cruz Rojo, Charlene Da Silveira, John Arne Dahl, Etienne De Montmollin, Cristina De Rose, Fernanda Dias Da Silva, Thomas Drake, Amiel A Dror, Anne Margarita Dyrhol-Riise, Linn Margrete Eggesbø, Mohammed El Sanharawi, William Finlayson, Aline-Marie Florence, Linda Gail Skeie, Noelia García Barrio, Anatoliy Gavrylov, Louis Gerbaud Morlaes, Yanay Gorelik, Mette Stausland Istre, Silje Bakken Jørgensen, Karl Trygve Kalleberg, Beathe Kiland Granerud, Eyrun Floerecke Kjetland Kjetland, Gry Kloumann Bekken, Galyna Kutsyna, Nadhem Lafhej, Cyril Le Bris, Georges Le Falher, Lucie Le Fevre, Quentin Le Hingrat, Marion Le Maréchal, Soizic Le Mestre, Gwenaël Le Moal, Hervé Le Nagard, Sophie Letrou, Wei Shen Lim, Andreas Lind, Carlos Lumbreras Bermejo, Miles Lunn, Olga Martynenko, Roberta Meta, Lina Morales Cely, Clara Mouton Perrot, Alamin Mustafa, Karl Erik Müller, Ebrahim Ndure, Anders Benteson Nygaard, Claudia Milena Orozco-Chamorro, Paul Otiku, Miguel Pedrera Jiménez, Frank Olav Pettersen, Chiara Piubelli, Víctor Quirós González, Else Quist-Paulsen, Dag Henrik Reikvam, Antonia Ricchiuto, Aleksander Rygh Holten, Nadia Saidani, Pablo Serrano Balazote, Nassima Si Mohammed, Lene Bergendal Solberg, Edouard Soum, Elisabetta Spinuzza, Trude Steinsvik, Birgitte Stiksrud, Mathew Thorpe, Vadim Tieroshyn, Kristian Tonby, Anders Tveita, Sylvie Van Der Werf, Paul Henri Wicky, Ibrahim Richard Bangura, Leonardo Bastos, Daniel Cassaglia, Barbara Citarella, Sarah Duque, Anne Margarita Dyrhol Riise, Annelies Gillesen, Bronner P Goncalvez, Margareta O’Hara, Lars Hegelund, Aquiles Henriquez Trujillo, Elsa D Ibañez, Jane Ireson, Oksana Krugalova, Sam Lissaeur, Sinnadurai Manohan, Prasan K Panda, Daniel R Plotkin, Liliana Resende, Sergio Ruiz Saltana, Steffi Ryckaert, Girish Sindhwani Pulm, and Caroline Vika

Subjects
Medicine (General), R5-920, Infectious and parasitic diseases, RC109-216
Abstract

Introduction A proportion of people develop Long Covid after acute COVID-19, but with most studies concentrated in high-income countries (HICs), the global burden is largely unknown. Our study aims to characterise long-term COVID-19 sequelae in populations globally and compare the prevalence of reported symptoms in HICs and low-income and middle-income countries (LMICs).Methods A prospective, observational study in 17 countries in Africa, Asia, Europe and South America, including adults with confirmed COVID-19 assessed at 2 to

Published
2024
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47. Utility of a high-intensity interval training app as a remote exercise support strategy in children with obesity: An exploratory study of adherence, effect, and perceptions of its use

Author

Fábio de Freitas, Maria Ângela Antônio, Mariana R Zago, Mariana Zambon, and António Videira-Silva

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Objective This study aimed to explore the utility of a high-intensity interval training (HIIT) app as a remote exercise support strategy in children with obesity through assessing adherence, possible effects on obesity-related outcomes, and perceptions of its use to support counseling and improve the treatment of children with obesity. Methods Thirty-seven children (94.6% with obesity; 45.9% girls), with a mean age of 10.4 (±1.8) years and a mean body mass index (BMI) z-score of 3.31 (±1.09) were recruited to use the app during 6 weeks. Assessments were performed at baseline, 6 (end of intervention), and 12 weeks (follow up). Results Thirty-two (86.3%) participants completed both intervention and follow-up assessments and were analyzed. On average, children used the HIIT app 2.5 times per week (95% confidence interval (CI): 1.9 to 3.0), with the highest perceived exertion of 4.1 (95% CI: 3.6 to 4.5). No over-time differences were found in body composition, physical activity, screen time, sleep duration, or water intake after the intervention; however, an over-time decrease in sugary beverages intake (Δ−0.9, 95% CI: −1.6 to −0.1, p = .019). No differences in body composition were found at follow up. Although none of the children or parents perceived impairments in nutritional behavior, general wellbeing, or fitness as a consequence of intervention, most children (64.5%), but not parents, perceived improvements in nutritional behavior and general wellbeing. Conclusion Although feasible, the 6-week effect of HIIT app use is modest or absent regarding body composition, movement, and nutritional behavior change, probably due to its low volume. More studies are needed to explore the utility of HIIT apps as a remote exercise support strategy for children with obesity further.

Published
2024
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48. Corrigendum: The temporal variability of Io’s hotspots

Author

A. Mura, F. Zambon, F. Tosi, R. M. C. Lopes, J. Rathbun, M. Pettine, A. Adriani, F. Altieri, M. Ciarniello, A. Cicchetti, G. Filacchione, D. Grassi, R. Noschese, A. Migliorini, G. Piccioni, C. Plainaki, R. Sordini, G. Sindoni, and D. Turrini

Subjects
Io, Galilean moons of Jupiter, volcanism, infrared-IR, Juno, Astronomy, QB1-991, Geophysics. Cosmic physics, QC801-809
Published
2024
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