Improvements in Statistical Model Checking: Estimation, Optimization, Parallelization

The size and complexity of the technological solutions we now design to tackle the problems of our modern world have increased tremendously. From medical robots to autonomous cars, the products of innovation must now carry out missions that are not only of critical importance but also come with strict requirements and high expectations. For a long time, engineers have been developing new theories and tools to improve the verification of complex software and large systems. Beyond basic testing and code reviewing, formal methods can offer absolute guarantees with respect to the properties of interest in an automated fashion. However, they suffer from a fundamental limitation: they do not scale well and can seldom be used for real-world applications. Statistical Model Checking (SMC) combines the rigorous framework of standard model checking with sampling and statistical algorithms to avoid that issue. Over the last thirty years, SMC has grown into a mature and promising field of research, yet many challenges remain. This thesis explores multiple paths to improve SMC, providing new insight and solutions to these challenges. We first study adaptive stopping algorithms as an alternative to basic sampling approaches and classic Monte Carlo algorithms. We show how they can significantly reduce the number of simulations that are required for the verification of a system, enhancing the scalability of SMC methods even further. We illustrate their efficiency with the rare event problem. Next, we propose an update to the Smart Sampling algorithm and describe the structure of a genetic algorithm for the optimization of schedulers for Markov decision processes. We then investigate the importance of parallelization as a practical solution to the scalability limitations of SMC. Finally, we expand SMC to a new class of models with temporal networks to analyze the robustness of task networks with data from NASA’s Perseverance rover and from the biomanufacturing industry.(FSA - Sciences de l'ingénieur) -- UCL, 202

PHYSIOLOGICAL AND MOLECULAR RESPONSES OF TEXTILE HEMP (Cannabis sativa Santhica 27) TO CADMIUM AND ZINC, WITH A PARTICULAR FOCUS ON THE ANALYSIS OF SILICON-INDUCED PROTECTION MECHANISM.

Soil contamination by heavy metals, particularly cadmium and zinc, represents a major environmental and health concern, exacerbated by industrial, mining, and agricultural activities. Phytoremediation, an ecological and cost-effective strategy, leverages plants to extract or stabilize these pollutants. Textile hemp (Cannabis sativa L. var. Santhica 27) is a promising candidate for this approach due to its deep root system, high biomass production, and non-food applications. Although silicon is not an essential element for plant growth, it has been shown to enhance tolerance to abiotic stresses. This study investigates the effect of silicon on the response of textile hemp exposed to cadmium and zinc contamination in a highly bioavailable hydroponic system. Silicon was supplied in hydroponic solution as 2 mM metasilicic acid, ensuring full phytoavailability. One week later, cadmium (20 µM) and zinc (100 µM) were introduced. A multidisciplinary approach was used, integrating molecular (proteomic), biochemical, and physiological analyses – including pigment composition, hormonal profiling, and gas exchange measurements – to better understand the adaptation and accumulation mechanisms of hemp in a phytoremediation context. Contrary to numerous studies highlighting the beneficial role of silicon in mitigating abiotic stress, our results indicate no protective effect and even potential negative impacts on certain physiological mechanisms. Specifically, silicon application led to a reduction in chlorophyll and certain carotenoid concentrations, with no significant improvements in physiological parameters. These findings suggest that silicon does not enhance the tolerance of textile hemp to cadmium and zinc stress, potentially due to the plant’s relatively low silicon accumulation capacity

Distinction and Identity in Late-Scholastic Thought and Beyond

This volume aims to document the historical emergence of the various types of distinctions in medieval philosophy, highlighting in particular the emergence of the Formalist tradition that had its roots in the works of the Franciscan John Duns Scotus († 1308) and his early followers. This literature enjoyed vast diffusion during the Renaissance and still played a significant role in textbooks of scholastic philosophy in the seventeenth and eighteenth centuries. It framed the early-modern debates about the distinction between body and mind or matter and extension. This book provides an important case for a much-needed revision of the relationship between “Medieval” and “Early Modern” philosophy – these categories are too often used to signal some fundamental divide in intellectual history, where in fact there was continuity. It deals with many figures who have been little studied to date as well as canonical thinkers such as Francisco Suárez and Gottfried Wilhelm Leibniz

La gestion des matières communautaires à Bruxelles : repenser les termes du dilemme communautaro-régional pour mieux répondre aux besoins sociaux et de santé des Bruxellois

Discussion des contributions d'Hugues Dumont sur le fédéralisme à Bruxelles et le modèle communautair

Genetic Variation and Ultrafiltration with Peritoneal Dialysis: A Genome-Wide Association Study.

There is a large person-to-person variability in ultrafiltration volume with peritoneal dialysis (PD), most of which cannot be accounted for by demographic and clinical differences. Herein we tested the hypothesis that common genetic variants are associated with peritoneal ultrafiltration and explored one mechanistic pathway identified by genetic studies. We generated estimates of heritability and undertook genome-wide and gene-wise studies, adjusted for peritoneal solute transfer rate (PSTR), to test associations of genetic variation with ultrafiltration on peritoneal equilibration test (PET) done at PD initiation in 2723 participants in the international Bio-PD study. We used a mouse model of PD to study the mechanistic basis for the association of PTGES gene with peritoneal ultrafiltration. PET was done at a median of 61 days (IQR 38-118) from PD start with a median 4-hour ultrafiltration volume of 250 mL (IQR 25-465). The heritability of peritoneal ultrafiltration was estimated to be 50% (p=0.001). In single nucleotide variant (SNV)-wise multi-ancestry GWAS using TRACTOR software, one SNV reached genome-wide significance in participants with European local ancestry (rs72631501, CRK intron, p=2.6x10-8) and one in participants with South Asian local ancestry (rs1416265, intergenic, p=4.2x10-8). Gene-wise analyses showed significant association of 21 genes at false discovery rates (FDRs) <0.10 in the European strata, notably PTGES (FDR=0.053), SLC24A3 (FDR=0.0003) and CRK (FDR=0.04). SLC24A3 remained significant (FDR=0.03) in meta-analysis of the four ancestry strata. Using scRNAseq, PTGES localized in peritoneal adipocytes. In a mouse PD model, pharmacological modulation of PTGES altered dialysate prostaglandin E2 (PGE2) levels with changes in adipocyte volume, peritoneal small solute transfer rate, and ultrafiltration volume. Common genetic variants accounted for a substantial proportion of the variability in peritoneal ultrafiltration with potential associations with 21 genes, including CRK, PTGES and SLC24A3. Functional studies substantiated a potential role for PTGES/PGE2 in regulating peritoneal ultrafiltration

Implementation of Soft Restrictions to Improve Neural Networks Robustness in Chemical Kinetics Time Integration

This work presents insights into the implementation of common soft-restrictions used for chemical kinetics time-integration, and analyzes potential issues and specific problems that arise during their implementation

Conversational AI and Chatbots

Conversational AI includes chatbots, dialogue systems, intelligent personal assistants, and other conversational agents used for dialogue practice, whether spoken or written, for language learning. This chapter explores the role of conversational AI, from its rule-based origins to the advent of large language models (LLMs), in language learning. It examines the theoretical foundations underpinning the use of chatbots for language learning, including the Interaction Hypothesis and the impact on foreign language anxiety and willingness to communicate. The chapter synthesizes empirical evidence regarding the effectiveness of both dedicated language learning applications and general-purpose conversational AI for autonomous practice and integration into formal teaching contexts. Finally, it provides practical recommendations for teachers, addressing guidance strategies, professional development, tool selection, activity design, and potential challenges in using conversational AI to support language development

Opportunistic TCP-AO with TLS

This document specifies an opportunistic mode for TCP-AO. In this mode, the TCP connection starts with a well-known authentication key which is later replaced by a secure key derived from the TLS handshake

Gallium based hollow silica nanospheres for the acid-catalyzed upgrading of glycerol: Enhanced activity disclosed via an in-depth nuclear magnetic resonance approach

Ga-doped hollow silica nanosphere and nanotubes were synthetized using a soft template sol–gel method. The low dimensional morphologies (0D or 1D) were obtained by simply adjusting the stirring speed during the synthesis procedure. The two materials were fully characterized using different techniques such as ssNMR, N2 physisorption, XRD, TEM or ICP-OES. The influence of the calcination temperature on the coordination environment of gallium as well as the accessibility of the gallium active sites was proved via 71Ga ssNMR. The acid features of the solids were studied via a combined approach based on FT-IR of adsorbed ammonia and 31P ssNMR using trimethylphosphine as a probe molecule. The latter technique allows unveiling a higher Brønsted/Lewis acid sites ratio of Ga-nanospheres as compared to Ga-nanotubes, probably as a consequence of the more defective spherical shell. Both nanostructures were tested for the conversion of glycerol to solketal. Ga-nanospheres revealed improved catalytic performance in comparison with the corresponding nanotubes and displayed outstanding activity with respect to other solid catalysts reported in the literature and tested under the same reaction conditions. Moreover, they proved to be stable and reusable in multiple cycles. The E-factor calculated under the best condition was below 1 thus proving the sustainability of the process