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Excited-state lifetimes in <math><mmultiscripts><mi>In</mi><mprescripts/><none/><mn>131</mn></mmultiscripts></math>, <math><mmultiscripts><mi>Sn</mi><mprescripts/><none/><mn>131</mn></mmultiscripts></math>, and <math><mmultiscripts><mi>Te</mi><mprescripts/><none/><mn>136</mn></mmultiscripts></math> measured with the HiCARI <math><mi>γ</mi></math>-ray spectrometer at RIBF at RIKEN
No full textInternational audienceIn the years 2020 to 2021, a high resolution in-beam γ-ray spectroscopy campaign took place at the Radio Isotope Beam Factory within the frame of the HiCARI project. An array composed of 12 composite Ge detectors of different types was put together by an international collaboration in order to address a variety of physics cases of interest, in many cases by measuring excited-state half-lives using Doppler-shift techniques. The analysis of the Doppler-shifted lineshapes observed for the 988-keV, 3/2−→1/2− and 1655-keV, 5/2+→3/2+ spin-flip M1 transitions in In131 and Sn131, respectively, the 332-keV, 1/2+→3/2+l-forbidden M1 transition in Sn131, as well as the 607-keV, 21+→01+ decay in Te136 allowed to characterize this new detector array and to establish a valid analysis procedure. The extracted half-lives are compared to previously reported results as well as theoretical calculations
Un employeur dans la ville
No full textNational audienceDans le cadre intellectuel du modèle de la ville attractive, le fait de disposer d’une université sur son territoire est considéré comme un facteur de rayonnement dans la compétition interurbaine. Si les difficultés croissantes (et bien réelles) d’accès au logement des étudiants sont devenues un marronnier journalistique de chaque rentrée, une université est également un employeur dont les agents doivent eux-aussi se loger. Où vivent ceux de l’université de Nantes
Histological pattern of non-infectious thoracic aortitis impacts mortality
No full textInternational audienceBackground: Non-infectious aortitis encompasses various histological patterns, but their specific cardiovascular outcomes remain unclear.Objective: To evaluate the mortality associated with non-infectious surgical thoracic aortitis.Methods: This retrospective multicenter study included patients who underwent thoracic aortic surgery and had histological evidence of aortitis. The study analyzed the characteristics of patients with non-infectious aortitis presenting either a granulomatous/giant cell histological pattern or a lymphoplasmacytic pattern. Factors associated with mortality were identified using multivariate analysis.Results: Among 5666 patients who underwent thoracic aortic surgery, 197 were found to have non-infectious aortitis with either a granulomatous/giant cell histological pattern (n = 138) or a lymphoplasmacytic pattern (n = 59). The overall standardized mortality rate (SMR) for patients with non-infectious surgical thoracic aortitis was 1.61 (95 % CI: 1.05; 2.39), with 31.5 % of patients dying within 10 years of the initial procedure. After a median follow-up of 3.5 years [IQR: 0.5-6.8] post-surgery, 31 % of deaths were due to aortic dissection or rupture. The 10-year cumulative incidence of death was 40.1 % (95 % CI, 17.7-61.8) for patients with a granulomatous/giant cell pattern and 14.4 % (95 % CI, 2.6-35.6) for those with a lymphoplasmacytic pattern. Granulomatous/giant cell histological pattern (HR 4.71 [vs lymphoplasmacytic pattern]; 95 % CI, 1.37-16.2; p = 0.023) and aortic dissection at diagnosis (HR 6.07 [vs aneurysm]; 95 % CI, 2.89-12.7; p < 0.0001) were independently associated with increased mortality.Conclusion: This multicenter study found that 31.5 % of patients with non-infectious surgical thoracic aortitis are expected to die within 10 years of their initial surgery. The granulomatous/giant cell histological pattern is associated with higher mortality
AAPP | Atti della Accademia Peloritana dei Pericolanti
No full textInternational audienceIn this short note, we survey several results concerning the structure of certain graphs, introduced by the fourth-named author, that can be associated to groups and gyro-groups, which are algebraic structures satisfying a twisted form of associativity. Furthermore, we include an original result, showing that the so-called Ḡ-gyro-graph associated to a gyro-group Ḡ endowed with a subset S ⊂ Ḡ is connected if and only if S is a left generating set of Ḡ. Moreover some properties and examples of both G-graphs and Ḡ-gyro-graphs are presented.</div
Copper-decorated Biochar derived from sludge as eco-friendly nano-catalyst for efficient p-nitrophenol reduction
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The Development of a Kinetic Model for Biochar Gasification with CO2: Comparison Between a Thermogravimetric Analyzer and a Fluidized Bed Reactor
No full textInternational audienceThis study presents the development of a kinetic model for the gasification of biochar with carbon dioxide and compares the results obtained using a thermogravimetric analyzer (TGA) and a fluidized bed reactor (FBR). The kinetic experiments investigated the effects of the CO2 partial pressure (0.33–1 atm), temperature (800–1000 °C), and CO2/C ratio (3.5–10.5). Three structural models, the shrinking core model (SCM), volumetric model (VM), and power-law model (PLM), were evaluated for their ability to predict experimental results. The results demonstrated that increasing the temperature, CO2 partial pressure, and CO2/C ratio enhanced the gasification rate, reducing the time required for complete biochar conversion. The apparent activation energy for both reactors was similar (156–159 MJ/kmol), with reaction orders of 0.4–0.49. However, the kinetic models varied significantly between setups. In the TGA, the PLM provided the best fit to experimental data, with standard deviations of 2.6–9%, while in the FBR, the SCM was most accurate, yielding an average deviation of 1.5%. The SCM effectively described the layer-by-layer char consumption, where gasification slowed at high conversion levels. Conversely, the PLM for the TGA revealed a unique mathematical function not aligned with traditional models, indicating localized reaction behaviors. This study highlights the inability to directly extrapolate TGA-derived kinetic models to FBR systems, underscoring the distinct mechanisms governing char consumption in each reactor type. These findings provide critical insights for optimizing biochar gasification across diverse reactor configurations
Advancing agroecology and sustainability with agricultural robots at field level: A scoping review
No full textInternational audienceAgricultural robots show a growing potential to improve resource management and reduce the environmental impacts of farming. However, the evaluation of robots’ contribution to support sustainable farming is still lacking. This study specifically reviewed the operationalization of four agroecological principles at the field level: recycling, soil health, biodiversity and synergy. To this aim, a scoping review was conducted on the Scopus database, with a query within titles, abstracts, and author keywords mentioning robots, and agroecology or sustainability. The body of literature was screened to include only open field robots. The resulting 78 documents were coded inductively on three macro areas: (1) academic background, (2) robot operations, (3) contribution to agroecology principles, whether explicitly or implicitly mentioned. The results highlight that robots operationalize agroecology principles through non-chemical and selective weeding to preserve diversity and soil health, lighter designs that reduce soil compaction, and advanced data collection systems to optimize resource use and synergy. Solar-powered robots represent early steps toward recycling, but this principle remains understudied. The discussion expands on the potential of robotics in other innovative approaches for sustainable agriculture, such as agroforestry, conservation agriculture, and novel farming system design. Key challenges include ensuring farmers are enabled to master data collection and management, as well as integrating high-tech robotics with low-tech solutions. These efforts are critical for leveraging agricultural robotics to advance agroecology and sustainability across diverse farming systems
Graph Neural Network Based on Molecular and Pharmacophoric Features for Drug Design Applications
No full textInternational audienceResearch fields that leverage relational data, like many others, have been significantly impacted by Deep Learning (DL) techniques, particularly Graph Neural Networks (GNNs). Among these fields, drug design, which aims to create new molecules with optimal affinities for specific targets, is a crucial step in the development of new medicinal drugs. In silico approaches in this area often rely on molecular graphs that encode the atoms and bonds of a molecule, without prior knowledge of the biological properties to be predicted. To address this limitation, pharmacophoric features are essential, as they contain structural information that captures important biological properties. These features have proven effective in tasks involving protein-ligand interactions. In this context, we propose the MCP-GNN model, which combines molecular representations with complete graphs of pharmacophoric features, both based on 2D information, to classify biological activity. Our experimental results demonstrate that this approach, using simple yet efficient techniques, achieves better performance than more complex architectures.</div
New challenges and perspectives on the organic halo effect on calories estimation: A brief review and Meta-analysis
No full textInternational audienceOrganic certification identifies food produced with more sustainable product methods. However, several studies have pointed out that it is also likely to generate a halo effect on the caloric estimation of food. As a result, unhealthy foods are perceived as containing fewer calories and may lead to increased consumption intentions. The aim of this paper is to quantify the magnitude of this organic halo effect and identify its possible moderators. We address the issue with a systematic review and a meta-analysis of the available literature specifically focused on the organic halo effect on food calorie estimation (i.e., 10 articles, 21 studies). The results highlighted a strong “organic halo effect” on calorie estimation (r = 0.40). Despite these findings, no stable moderator of the organic halo effect has been consistently identified across the literature. This meta-analysis provides a foundation for future research on the organic halo effect, offering a framework to guide upcoming studies on the phenomenon. The discussion outlines research avenues and advocates for a systematic investigation of specific moderators as well as an investigation of the conditions that promote the organic halo effect to facilitate and structured the exploration of the phenomenon