Dualisme: transparence fiscale accrue et maintien de la sphère privée

Dans ce travail, je me suis penchée sur un sujet d’actualité qui touche la Suisse et un de ses secrets les mieux gardé disait-on ; le secret bancaire. Depuis des siècles, la Suisse a mis en place un système bancaire régit par des pratiques et coutumes, puis par des lois qui ont permis la non-divulgation des détenteurs et ayants droit économiques des comptes bancaires. Depuis toujours celui-ci a été contesté et critiqué par les pays étrangers mais il a su garder sa place et son importance au sein de la politique et législation suisse jusqu’à récemment. En effet, ces dernières années ont été synonyme de crise économique sans précédent et les places financières internationales ont du remettre en question leurs méthodes de contrôles fiscaux. La crise financière de 2008 a eu un impact sur l’économie mondiale ainsi que sur la politique et la légalisation suisse des marchés financiers. Les banques doivent désormais coopérer avec les Etats étrangers suite aux accords signés par le Conseil Fédéral, affaiblissant ainsi le secret bancaire. La sphère privée est-elle donc toujours intouchable en Suisse? Ce travail est structuré en trois parties ; du passé au présent, du présent au futur proche et le futur lointain. Dans la première partie, j’aborderai les notions de base entourant le secret bancaire et comment nous sommes arrivés aujourd’hui à le remettre en question. Dans la seconde partie, j’analyserai les impacts pour les banques et les clients dans un futurproche. Et dans la troisième partie, je souhaiterai mettre en avant les conséquences sur le long terme qui découleront de ces nouvelles réglementations. Je finirai par une conclusion qui reprendra les thèmes abordés tout au long de mon travail

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Persistent headaches one year after bacterial meningitis: prevalence, determinants and impact on quality of life

International audienceBackground: Little is known on headaches long-term persistence after bacterial meningitis and on their impact on patients' quality of life.Methods: In an ancillary study of the French national prospective cohort of community-acquired bacterial meningitis in adults (COMBAT) conducted between February 2013 and July 2015, we collected self-reported headaches before, at onset, and 12 months (M12) after meningitis. Determinants of persistent headache (PH) at M12, their association with M12 quality of life (SF 12), depression (Center for Epidemiologic Studies Depression Scale) and neuro-functional disability were analysed.Results: Among the 277 alive patients at M12 87/274 (31.8%), 213/271 (78.6%) and 86/277 (31.0%) reported headaches before, at the onset, and at M12, respectively. In multivariate analysis, female sex (OR: 2.75 [1.54-4.90]; p < 0.001), pre-existing headaches before meningitis (OR: 2.38 [1.32-4.30]; p < 0.01), higher neutrophilic polynuclei percentage in the CSF of the initial lumbar puncture (OR: 1.02 [1.00-1.04]; p < 0.05), and brain abscess during the initial hospitalisation (OR: 8.32 [1.97-35.16]; p < 0.01) were associated with M12 persistent headaches. Neither the responsible microorganism, nor the corticoids use were associated with M12 persistent headaches. M12 neuro-functional disability (altered Glasgow Outcome Scale; p < 0.01), M12 physical handicap (altered modified Rankin score; p < 0.001), M12 depressive symptoms (p < 0.0001), and M12 altered physical (p < 0.05) and mental (p < 0.0001) qualities of life were associated with M12 headaches.Conclusion: Persistent headaches are frequent one year after meningitis and are associated with quality of life alteration

One-Year Sequelae and Quality of Life in Adults with Meningococcal Meningitis: Lessons from the COMBAT Multicentre Prospective Study

Trial registration: ClinicalTrial.Gov identification number NCT01730690.International audienceIntroduction: COMBAT is a prospective, multicentre cohort study that enrolled consecutive adults with community-acquired bacterial meningitis (CABM) in 69 participating centres in France between February 2013 and July 2015 and followed them for 1 year.Methods: Patients aged at least 18 years old, hospitalised with CABM were followed during their hospitalisation and then contacted by phone 12 months after enrolment. Here we present the prevalence of sequelae at 12 months in a subgroup of patients with meningococcal meningitis.Results: Five of the 111 patients with meningococcal meningitis died during initial hospitalisation and two died between discharge and 12 months, leaving 104 patients alive 1 year after enrolment, 71 of whom provided 12-month follow-up data. The median age was 30.0 years and 54.1% of the patients had no identified risk factor for meningitis. More than 30% reported persistent headache, more than 40% were not satisfied with their sleep and 10% had concentration difficulties. Hearing loss was present in about 15% of the patients and more than 30% had depressive symptoms. About 13% of the patients with a previous professional activity had not resumed work. On the SF-12 Health Survey, almost 50% and 30% had physical component or mental component scores lower than the 25th percentile of the score distribution in the French general population. There was a non-significant improvement in the patients' disability scores from hospital discharge to 12 months (p = 0.16), but about 10% of the patients had residual disability.Conclusions: Although most patients in our cohort survive meningococcal meningitis, the long-term burden is substantial and therefore it is important to ensure a prolonged follow-up of survivors and to promote preventive strategies, including vaccination

Relationship between serotypes, disease characteristics and 30-day mortality in adults with invasive pneumococcal disease

International audienc

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License