HAL-Artois
Not a member yet
27242 research outputs found
Sort by
SIMPLICIAL INTERSECTION HOMOLOGY REVISITED
No full textInternational audienceIntersection homology is defined for simplicial, singular and PL chains. In the case of a filtered simplicial complex, it is well known that the three versions are isomorphic. This isomorphism is established by using the PL case as an intermediate between the singular and the simplicial situations. Here, we give a proof similar to the classical proof for ordinary simplicial complexes. We also study the intersection blown-up cohomology that we have previously introduced. In the case of a pseudomanifold, this cohomology owns a Poincaré isomorphism with the intersection homology, for any coefficient ring, thanks to a cap product with a fundamental class. We prove that the simplicial and the singular blown-up cohomologies of a filtered simplicial complex are isomorphic. From this result, we can now compute the blown-up intersection cohomology of a pseudomanifold from a triangulation. Finally, we introduce a blown-up intersection cohomology for PL-spaces and prove that it is isomorphic to the singular ones. We also show that the cup product in perversity 0 of a CS-set coincides with the cup product of the singular cohomology of the underlying topological space
"Un désir de voir plus clair": dispositif théologique et innovation sociologique des maîtres aux XIIIe-XVe siècles
No full textPre-print versionInternational audienc
Π-NeSy: A Possibilistic Neuro-Symbolic Approach
No full textIn this article, we introduce a neuro-symbolic approach that combines a low-level perception task performed by a neural network with a high-level reasoning task performed by a possibilistic rule-based system. The goal is to be able to derive for each input instance the degree of possibility that it belongs to a target (meta-)concept. This (meta-)concept is connected to intermediate concepts by a possibilistic rule-based system. The probability of each intermediate concept for the input instance is inferred using a neural network. The connection between the low-level perception task and the high-level reasoning task lies in the transformation of neural network outputs modeled by probability distributions (through softmax activation) into possibility distributions.The use of intermediate concepts is valuable for the explanation purpose: using the rule-based system, the classification of an input instance as an element of the (meta-)concept can be justified by the fact that intermediate concepts have been recognized.From the technical side, our contribution consists of the design of efficient methods for defining the matrix relation and the equation system associated with a possibilistic rule-based system. The corresponding matrix and equation are key data structures used to perform inferences from a possibilistic rule-based system and to learn the values of the rule parameters in such a system according to a training data sample. Furthermore, leveraging recent results on the handling of inconsistent systems of fuzzy relational equations, an approach for learning rule parameters according to multiple training data samples is presented. Experiments carried out on the MNIST addition problems and the MNIST Sudoku puzzles problems highlight the effectiveness of our approach compared with state-of-the-art neuro-symbolic ones
Degradative removal of diclofenac from wastewater - Statistical and analytical approaches to understand degradation pathways
No full textInternational audienceIn environmental management area, quality of water is a major growing concern with the emerging contaminants such as pesticides and pharmaceuticals likely to be present at low concentrations in water bodies, thereby potentially harming the ecosystem and human health. Diclofenac (DCF), a commonly used drug, has been found in wastewater, surface water, and drinking water sources, whose elimination can be a challenge issue. This study investigates the elimination of DCF by the photochemical method from aqueous media using short-wavelength radiation and hydrogen peroxide. A statistical approach is used to optimize and evaluate the effects of experimental parameters on the degradation of DCF. A quadratic model was proposed to predict the response to variations in three key parameters viz., initial DCF concentration, pH of the solution, and H2O2 concentration. The suggested model shows a high coefficient of determination (R2 = 0.9961), indicating that observed data is replicated by modelled data. The findings suggest that pH of the solution is the most significant factor affecting the degradation process. Furthermore, a strong interaction between initial concentrations of DCF and hydrogen peroxide is observed. Complete degradation of DCF is achieved within 90 min under the optimal conditions (pH = 4, [DCF]0 = 20 mg L−1, and [hydrogen peroxide]0 = 600 mg L−1). This is the first of its kind of study to identify the reaction intermediates using the solid phase extraction (SPE), a pre-concentration step via evaporation with a gentle stream of nitrogen, and direct infusion high-resolution mass spectrometry (DI-HRMS) to detect trace level reaction intermediates. The study follows the United Nations SDGs # 7 program dealing with clean water production. The possible degradation pathways of DCF are proposed
Motivational factors influencing the choice of oncology as a specialty among French medical students
No full textInternational audienceBackground: There is limited data regarding what motivations are behind the choice of oncology (both medical oncology and radiation oncology) as a specialty among medical students. Therefore, the aim of this study is to identify the factors that motivate medical students to choose oncology as a specialty.Methods: Medical students of classes 2022 and 2023 in the Universities of Lille and Amiens (North of France) were enrolled in a quantitative online survey. Chi-square automatic interaction detection (CHAID) and binary and multiple linear regressions were performed to identify the factors that determine the choice of specialty among the students.Results: Among 563 respondents (response rate: 45%) who participated in the survey, 14, 13, and 14 were considering oncology as their first (2.5%), second (2.3%), and third (2.5%) specialty choices, respectively. The CHAID analysis retained two factors: "rotation in the medical oncology unit" (p < .0001) and "identification with a physician practicing the desired specialty" (p = 0.049). The factors identified in the multivariate regression analysis (weighted according to first, second, or third choices) differed according to sex. In men, rotation in a radiation oncology unit (β = 0.190; p < 0.001) or a medical oncology unit (β = 0.227; p = 0.010) and interest in fundamental research (β = 0.063; p < 0.001) were positively associated with choosing oncology as a specialty, whereas working in rural areas (β=-0.094; p = 0.014) was negatively associated with choosing oncology as a specialty. In women, rotation in a medical oncology unit (β = 0.289; p < 0.001), interest in cultivating a long-term relationship with patients (β = 0.129; p < 0.001), and interest in a hospital-based career (β = 0.214;p < 0.001) were positively associated with choosing oncology as a specialty; whereas desire to see the results of treatments quickly (β=-0.143; p = 0.018) and working in rural areas (β=-0.153; p = 0.006) were negatively associated with choosing oncology as a specialty.Conclusions: Experience during hospital rotations plays a crucial role in the specialty choices made by medical students. The motivations behind choosing oncology as a specialty differ according to gender. Intrinsic motivations (interests in fundamental research or in cultivating a long-term relationship with patients) and contextual factors (rural life or interest in a hospital-based career) influence the specialty choices of medical students
À l’école du planétaire humain
No full textInternational audienceFaire bouger des corps célestes incarnés par les corps humains : à l’école ou aucollège, pourquoi pas faire un planétaire humain pour engager les corps desélèves dans les apprentissages
Structural, Dielectric, and Ferroelectric Properties of BiFeO<sub>3</sub>/BaTiO<sub>3</sub> Superlattices
No full textInternational audienc
Environmental and genetic interactions underlying the morphological and genetic variability of the red juniper (Juniperus turbinata Guss.) in northeastern Morocco: implications for conservation
No full textInternational audiencePlant species often show morphological variations in response to their environments. In this study, we examined the trees, cones, seeds and leaves of three populations of Juniperus turbinata in north-eastern Morocco, located in littoral, semi-continental and continental zones, to evaluate how local conditions influence morphological character. Additionally, a genetic study using SSR markers was conducted to assess the genetic diversity and structure within these populations, aiming to determine the genetic contributions to observed morphological differences. The results showed significant morphological variation across zones. Cones from littoral population were larger and rounder, while those of the semi-continental and continental populations were more elongated and robust. Seeds and leaves characters also varied in patterns linked with altitude and aridity. Genetic analysis revealed moderate differentiation among populations, with higher genetic diversity in the continental site, as confirmed by several calculated indices such as the number of effective and private alleles, Shannon's information index, and observed and expected heterozygosities. Interestingly, the population structure profile identified two distinct genetic pools, with littoral and continental populations clustering closely together. This limited genetic differentiation likely due to gene flow or shared ancestry, suggests the formation of a single genetic group despite geographical separation. The results of this study show that the local environmental factors are the primary drivers of morphological variation, particularly in cones and seeds, while also highlighting a notable genetic component. These findings data are essential for defining conservation strategies adapted to local populations of J. turbinata in the context of climate change.</div
Aircraft Resource-Constrained Assembly Line Balancing with Learning Effect : a Constraint Programming Approach
No full textInternational audienceBalancing aeronautical assembly lines is a major challenge in modern aerospace manufacturing. Aircraft manufacturing plants typically have a predetermined production rate, but the production system requires a period of adaptation at start-up. This phenomenon, known as the learning effect, refers to the gradual improvement in efficiency through task repetition, thereby reducing task duration. However, the stability of an assembly line is also a critical factor, as any change in the production process incurs costs. In this study, Constraint Programming (CP) is used to optimise assembly line balancing, taking into account the learning effect to address the trade-off between achieving target production rates and minimising adjustments to the line
