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Correlation between damage parameters and mechanical proper-ties of concrete affected by ASR
Full text linkpeer reviewedTo investigate the potential correlation between damage parameters used to assess the level of alkali silica reaction (ASR) in concrete and the mechanical properties of the material is a promising approach. Currently, ASR damage evaluation of concrete is done following FHWA protocol [1]. The actual lev-el of damage (diagnosis) is evaluated using the Stiffness Damage Test (SDT) and the Damage Rating Index (DRI). Both methods provide parameters cor-related to the concrete's expansion level. In addition, future potential of damage (prognosis) is assessed using residual expansion tests in specific cli-matic conditions (R.H. >95 % and T = 38+/-°C) and alkaline solution (NaOH 1N, 38+/-°C). Expansion is thus currently used to assess the damage and predict future deterioration. However, only expansion measurements are in-sufficient for infrastructure managers who need to understand the structural impact of ASR on concrete structures. Therefore, this research aims to iden-tify new correlations between the actual test results and structural parameters of the concrete, providing more relevant information for infrastructure man-agement. In this project, cores from ASR-affected bridges were extracted, cut into samples and subjected to both prognosis and diagnosis tests, as well as compressive tests, directly after extraction and after expansion tests, respec-tively. A linear trend was identified for compressive strength, correlating with DRI values in cores tested after extraction, indirectly linking to the con-crete's expansion level. Young's modulus also decreased with additional ex-pansion during the tests, but no significant trendline was identified.Programme de coopération Wallonie-Bruxelles/Québec (2022-2024) : Valorisation des fines de recyclage et des cendres de biomasse dans les écoliants11. Sustainable cities and communitie
Modelling of fluvial dike breaching due to overtopping
Full text linkFluvial dikes are structures built along watercourses to protect humans and infrastructures from flooding. The risk of dike breaching is increasing due to more frequent extreme weather events, urbanization near these structures, and aging existing dikes. Among the causes of breaching, overtopping is the most common. Accurate prediction of the breaching dynamics and resulting flooding is crucial for effective emergency planning in floodplains.
This thesis focuses on developing a numerical model for homogeneous non-cohesive fluvial dike breaching induced by overtopping. While various models exist for dam breaching, these structures differ fundamentally from fluvial dikes. Embankment dams, which are perpendicular to the main flow, tend to breach symmetrically, whereas fluvial dikes mainly expand in the downstream direction due to the river momentum.
Building on an existing lumped model primarily designed for dam breaching, this work developed a new lumped model dedicated to fluvial dikes. A global sensitivity analysis and an uncertainty analysis applied on the initial dam model identified model parameters whose uncertainty had a critical impact on the variability of the model outputs, namely the breach discharge and expansion. Laboratory tests further clarified the influence of dike geometry and main channel width on breaching dynamics, suggesting that erosion at the downstream breach extremity is dictated by higher velocities than assumed in the initial dam model. This led to the introduction of an “effective breach width”, representing the fraction of the breach width conveying most of the water. Incorporating this concept considerably improved the model’s ability to predict the breach discharge and expansion.
However, accuracy on the breach discharge prediction remained limited, as it relied on simplified formulas borrowed from frontal weirs, which do not satisfactorily predict dike breach discharge. Various empirical or semi-empirical side weir formulations performed well for simplified side breach configurations but proved insufficient for dike breaching cases. Machine learning was then employed to better capture the breach hydrodynamics. A new analytical model was introduced and coupled to a decision-tree-based machine learning technique. This approach demonstrated strong performance in predicting the breach discharge from dike breaching laboratory tests.
The thesis also compared the adapted lumped model with its dynamic coupling to a 2D hydrodynamic model. Based on experimental observations and the global sensitivity analysis we conducted, the model parametrization was adjusted to further enhance breach erosion predictions. The adapted dike model outperformed the original dam model in predicting discharge and expansion for fluvial dike breach. It also provided more conservative flood extent predictions, as demonstrated for a hypothetical breach scenario along Belgium’s Albert Canal, making it particularly valuable for supporting evacuation planning in floodplains.
Future work should focus on additional test campaigns to refine the model structure and parametrization, enabling even greater accuracy in predicting fluvial dike breaching dynamics.Les digues fluviales, construites le long des cours d'eau, protègent les populations et les infrastructures contre les crues. Leur risque de rupture est en augmentation en raison du dérèglement climatique, de l'urbanisation croissante et du vieillissement des structures existantes. Prédire avec précision la dynamique de rupture et les inondations associées est essentiel pour une planification d'urgence efficace dans les zones inondables.
Cette thèse développe un modèle numérique dédié aux ruptures de digues fluviales homogènes et non cohésives induites par surverse. Contrairement aux barrages en remblai, qui sont perpendiculaires à l'écoulement principal et se rompent symétriquement, les brèches des digues s'étendent principalement dans la direction aval en raison de la quantité de mouvement importante de l’écoulement dans la rivière.
Dans cette thèse, un nouveau modèle non discrétisé spatialement et dédié aux digues fluviales a été mis au point à partir d’un modèle de rupture de barrages existant. Une analyse de sensibilité appliquée au modèle de rupture de barrage a permis d'identifier les paramètres dont l'incertitude a un impact important sur la variabilité du débit et de l'expansion de la brèche. Des essais en laboratoire ont permis de mieux comprendre l'influence de la géométrie de la digue et de la largeur du canal principal sur la dynamique de rupture. Il a également été mis en évidence que la vitesse de l’écoulement à proximité de l’extrémité aval de la brèche est sensiblement plus importante que la vitesse moyenne à travers la brèche. Cela a conduit à l'introduction d'une « largeur de brèche efficace », représentant la fraction de la brèche par laquelle transite la majeure partie du débit. L’utilisation de ce concept a considérablement amélioré les prédictions du modèle.
Cependant, la formulation du débit de brèche devait être revue car elle reposait sur des formules adaptées aux déversoirs frontaux, alors que la configuration étudiée correspond davantage à un déversoir latéral. Diverses formules empiriques de déversoirs latéraux ont été appliquées à des essais expérimentaux de rupture, mais leur précision s’est révélée insuffisante. Un nouveau modèle analytique a alors été introduit et couplé à une technique de machine learning basée sur les arbres de décision. Cette nouvelle approche a permis des prédictions du débit de brèche nettement plus précises.
Enfin, le nouveau modèle de rupture de digue a été comparé à son couplage avec un modèle hydrodynamique 2D. Avec une paramétrisation ajustée sur base d’observations expérimentales et de tests numériques, il s’est révélé plus fiable que le modèle de barrage, avec des prédictions plus conservatives, comme démontré dans un scénario de rupture hypothétique le long du canal Albert en Belgique.
De futurs travaux de recherche devraient inclure davantage d'essais expérimentaux, sur base desquels il serait possible d’affiner la structure et la paramétrisation du modèle et ainsi renforcer la précision des prévisions de rupture de digues fluviales
Delphi definition of general practice/family medicine specialty for a post-COVID world: in-person and remote care delivery.
Full text linkpeer reviewed[en] INTRODUCTION: The evolving landscape of general practice (GP)/family medicine (FM) in the post-COVID-19 era, focussing on integrating telemedicine and remote consultations requires a new definition for this specialty. Hence, a broader consensus-based definition of post-COVID-19 GP/FM is warranted.
METHODS: This study involved a modified electronic Delphi technique involving 27 specialists working in primary care recruited via convenient and snowball sampling. The Delphi survey was conducted online between August 2022 and April 2023, utilizing the Google Forms platform. Descriptive statistics were employed to analyse consensus across Delphi rounds.
RESULTS: Twenty-six international experts participated in the survey. The retention rate through the second and third Delphi rounds was 96.2% (n = 25). The broader consensus definition emphasizes person-centred care, collaborative patient-physician partnerships, and a holistic approach to health, including managing acute and chronic conditions through in-person or remote access based on patient preferences, medical needs, and local health system organization.
CONCLUSION: The study highlights the importance of continuity of care, prevention, and coordination with other healthcare professionals as core values of primary care. It also reflects the role of GP/FM in addressing new challenges post-pandemic, such as healthcare delivery beyond standard face-to-face care (e.g. remote consultations) and an increasingly important role in the prevention of infectious diseases. This underscores the need for ongoing research and patient involvement to continually refine and improve primary healthcare delivery in response to changing healthcare landscapes
A noise-robust acoustic method for recognizing foraging activities of grazing cattle
Full text linkpeer reviewedFarmers must continuously improve their livestock production systems to remain competitive in the growing dairy market. Precision livestock farming technologies provide individualized monitoring of animals on commercial farms, optimizing livestock production. Continuous acoustic monitoring is a widely accepted sensing technique used to estimate the daily rumination and grazing time budget of free-ranging cattle. However, typical environmental and natural noises on pastures noticeably affect the performance limiting the practical application of current acoustic methods. In this study, we present the operating principle and generalization capability of an acoustic method called Noise-Robust Foraging Activity Recognizer (NRFAR). The proposed method determines foraging activity bouts by analyzing fixed-length segments of identified jaw movement events produced during grazing and rumination. The additive noise robustness of the NRFAR was evaluated for several signal-to-noise ratios using stationary Gaussian white noise and four different nonstationary natural noise sources. In noiseless conditions, NRFAR reached an average balanced accuracy of 86.4%, outperforming two previous acoustic methods by more than 7.5%. Furthermore, NRFAR performed better than previous acoustic methods in 77 of 80 evaluated noisy scenarios (53 cases with p<0.05). NRFAR has been shown to be effective in harsh free-ranging environments and could be used as a reliable solution to improve pasture management and monitor the health and welfare of dairy cows. The instrumentation and computational algorithms presented in this publication are protected by a pending patent application: AR P20220100910. Web demo available at: https://sinc.unl.edu.ar/web-demo/nrfar
La bibliothèque de This et la production libraire copte dans l’Antiquité tardive : bilan et perspectives
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Peripheral myelin: From development to maintenance.
No full textpeer reviewedPeripheral myelin is synthesized by glial cells called Schwann cells (SCs). SC development and differentiation must be tightly regulated to avoid any pathological consequence affecting peripheral nerve function. Neuropathic symptoms can arise from developmental issues in SCs, as well as in adult life through processes affecting mature SCs. In this review we focus on SC differentiation from the immature towards the myelinating and non-myelinating SC stages, defining molecular mechanisms outlining radial sorting, a multi-stepped event essential for immature SC differentiation and myelination. We also describe mechanisms regulating myelin sheath maintenance and SC homeostasis during aging. Finally, we will conclude with some remaining questions in the field of SC biology
Lifespan quantitative MR images from 138 subjects, an open and spatially preprocessed dataset.
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Characterization, prediction, and remediation of salt-affected soils in the High Valley of Cochabamba - Bolivia
Full text linkIn a broad sense, soil salinity relates to high levels of soluble salts in the soil solution phase and soil sodicity refers to an excess of sodium in the exchangeable complex, while alkalinity indicates the dominance of alkaline salts and high pH. Salt-affected soils are mainly caused by natural conditions and/or anthropogenic activities and negatively affect plant growth and soil-water properties. The High Valley of Cochabamba - Bolivia is characterized by low soil and crop productivity, and land degradation primarily due to salinization processes, which in turn, are driven by semiarid conditions, population increase, deforestation, and inadequate agricultural practices. Some studies have been conducted primarily focused on mapping and characterizing salt-affected soils in this region, but there are still gaps in soil information, prediction tools, and amelioration techniques for their proper management. Therefore, this study aimed to contribute to the sustainable management and rehabilitation of salt-affected soils in the High Valley through baseline soil information, salinity/sodicity prediction models, and insights into amendment-based remediation techniques.
Regarding the characterization and classification of soil samples and profiles, the saline-sodic and saline classes dominate among the salt-affected soil samples, and most salt-affected soil profiles’ horizons showed high levels of salinity and sodicity. The alternative classification approach can overcome the confusion caused by the – USSL – saline-sodic soil class by considering the nature of soluble ions; in this context, some differences between the two methods, for salinity and sodicity distributions were observed. The spatial interpolation was unsatisfactory due to insufficient spatial correlation. Incorporating additional soil profiles and samples might improve the representativeness of the soil information, spatial prediction, and classification system.
Concerning the performance evaluation of machine learning models to predict soil salinity/sodicity variables, random forests (RF) and support vector machines (SVM) regressions outperformed the partial least squares algorithm in estimating soil ESP and ECe, as well as for predicting salt-affected soil classes. Multivariate regressions predicting soil ESP as a function of EC, SAR, and pH showed relatively good performance, somewhat similar to simple regression predicting ESP from SAR. The models to predict soil ESP and EC from remote sensing-based and geomorphometric features showed relatively low performance. Overall, these models might contribute to the monitoring and management of salt-affected soils in the High Valley; however, validations with additional samples and predictor variables are essential to improve their accuracy.
According to the first soil-column experiment assessing the effectiveness of individual mineral and organic amendments with leaching in remediating saline-sodic soils, gypsum was more effective than sulphur, while cattle/chicken manure was better than biochar and peat in lowering soil ESP, and any organic or mineral amendment was as efficient as water alone in decreasing soil ECe. The superiority of gypsum was mainly due to its Ca2+ content which displaces exchangeable Na+, while that of manure was probably due to its contribution of organic matter and divalent cations, which also improve soil-water properties. The second soil-column experiment evaluating the combined effect of manures and gypsum showed that either cattle or chicken manure together with gypsum at any dose was more effective than gypsum alone in reducing the soil ESP to below 5%; furthermore, except for water alone, all treatments were effective in lowering the soil ECe to below 1.6 dS m−1, and any combination was effective in decreasing soil pH to below 8.7. Thus, the effectiveness of manure combined with gypsum was mainly due to their synergistic effect on adsorbed Na+ displacement and soil structure improvement. The addition of manure might enhance and hasten the effect of gypsum with leaching in ameliorating saline-sodic/sodic soils. Further validation of the most effective amendment-based remediation techniques through field experiments is recommended, and alternative approaches such as biosaline agriculture and phytoremediation should also be explored.
In sum, the proper management and rehabilitation of salt-affected soils in the High Valley of Cochabamba relies on adequate characterization, correct classification, accurate estimation, and effective amelioration of these soils; consequently, this study contributes to these goals by providing: (1) comprehensive baseline soil information, (2) tailored prediction and classification tools, and (3) insights into amendment-based remediation techniques, all of which are subject to further refinement
The Clinical Relevance of Prior Metabolic and Bariatric Surgery in Alcohol-Related Liver Disease in a Nationwide Belgian Liver Transplant Population.
No full textpeer reviewed[en] BACKGROUND AND AIMS: Patients with a history of metabolic and bariatric surgery (MBS) are susceptible to developing alcohol use disorder. Outcome after transplantation for alcohol-related liver disease (ALD) has not been studied in-depth.
METHODS: We included adult patients who underwent a liver transplantation (LT) in Belgium between 1 January 2013 and 31 December 2022 for ALD. We captured all patients with a history of MBS prior to developing ALD, and included non-MBS patients for comparison.
RESULTS: We identified 39 patients who underwent MBS before developing ALD, and included 443 non-MBS patients with an LT for ALD as controls. The median time between MBS and diagnosis of severe liver disease was 7.2 years. MBS patients were 9 years younger at the time of transplantation (p < 0.001). Pre-LT hepatocellular carcinoma was more prevalent in the non-MBS group (p < 0.001), while severe bacterial infections occurred more frequently in those with prior MBS. Importantly, patients with MBS had a lower survival after LT in age- and sex-adjusted Cox regression analysis (HR 2.205, p = 0.023). Liver disease was listed in 70.0% versus 13.3% of patients as the main cause of death. Liver-related mortality was linked to alcohol use relapse post-LT, with significantly more MBS patients experiencing relapse (30.8% vs. 13.3%, p = 0.003).
CONCLUSION: Following MBS, excessive alcohol use can progress to end-stage ALD and need for LT. These patients present at a younger age, with more signs of hepatic decompensation, and can be at a higher risk for post-LT mortality, especially liver-related death