Scalable Bayesian nonparametric regression via a Plackett-Luce model for conditional ranks

We present a novel Bayesian nonparametric regression model for covariates X and continuous, real response variable Y. The model is parametrized in terms of marginal distributions for Y and X and a regression function which tunes the stochastic ordering of the conditional distributions F(y|x). By adopting an approximate composite likelihood approach, we show that the resulting posterior inference can be decoupled for the separate components of the model. This procedure can scale to very large datasets and allows for the use of standard, existing, software from Bayesian nonparametric density estimation and Plackett-Luce ranking estimation to be applied. As an illustration, we show an application of our approach to a US Census dataset, with over 1,300,000 data points and more than 100 covariates

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Éditorial -- Présence autochtone à la Maison Louis-Bertrand -- Le métissage au Bas-Saint-Laurent (1685-1849) -- Transformation du tissu urbain de la ville de Rimouski entre 1948 et 2004 -- La Buick Jouvin-Desrosiers -- SECTION SPÉCIALISÉE: Denis Riverin et la Compagnie des pêches sédentaires au Canada : les difficultés d'implantation d'une industrie de la pêche en Nouvelle-France (suite et fin) -- CHRONIQUES: Vieux écrits : La grande « détresse » de 1816 -- Des livres à lire

Rethinking business models for innovation

One of the major challenges confronted by those in charge of technological innovation involves anticipating the value creation model sufficiently early on,in a highly uncertain context both as far as the technology itself is concerned and the potential market. Today, in many industrial sectors, the innovation boundaries have moved towards projects that are more and more exploratory and fuzzy. The simple optimisation of linear processes of the "stage-gate" type is no longer sufficient to build sustainable competitive advantages. The notion of Business Models, when applied to innovation, enables us to describe how a company creates value through innovation, generally within a business ecosystem, and how the value will be distributed between the actors involved. The authors of this book believe that the notions of Business Modelling and value creation are key to all the dimensions of successful innovation, whether technology, marketing, organisational or economically based. Rethinking Business Models for Innovation: this title describes the relationship between thinking, modelling, and also field-testing. The book is based on a series of nine recent cases of innovation involving company managers, often assisted by researchers (the co-authors of each chapter), and how they built and formalised their Business Models and then tested their strategies. After having discovered the variety of the cases, the reader will understand that every innovation situation generates specific questions about Business Models. However, we feel that we can identify three key issues that arise, more or less, in each of these projects. The chapters in this book build on these issues: the identification of sources of value and revenue models (the notion of value creation), the position of the company in the value-network or ecosystem (the sharing of value) and finally the evolution of Business MoDdels over time (the sustainability and the competitiveness of the company). The last chapter goes over all the contributions, exploring the notion of value in the Business Model approach.business model ; innovation ; value ; entrepreneurial project

: Lessons from entrepreneurial projects

International audienceOne of the major challenges confronted by those in charge of technological innovation involves anticipating the value creation model sufficiently early on,in a highly uncertain context both as far as the technology itself is concerned and the potential market. Today, in many industrial sectors, the innovation boundaries have moved towards projects that are more and more exploratory and fuzzy. The simple optimisation of linear processes of the "stage-gate" type is no longer sufficient to build sustainable competitive advantages. The notion of Business Models, when applied to innovation, enables us to describe how a company creates value through innovation, generally within a business ecosystem, and how the value will be distributed between the actors involved. The authors of this book believe that the notions of Business Modelling and value creation are key to all the dimensions of successful innovation, whether technology, marketing, organisational or economically based. Rethinking Business Models for Innovation: this title describes the relationship between thinking, modelling, and also field-testing. The book is based on a series of nine recent cases of innovation involving company managers, often assisted by researchers (the co-authors of each chapter), and how they built and formalised their Business Models and then tested their strategies. After having discovered the variety of the cases, the reader will understand that every innovation situation generates specific questions about Business Models. However, we feel that we can identify three key issues that arise, more or less, in each of these projects. The chapters in this book build on these issues: the identification of sources of value and revenue models (the notion of value creation), the position of the company in the value-network or ecosystem (the sharing of value) and finally the evolution of Business MoDdels over time (the sustainability and the competitiveness of the company). The last chapter goes over all the contributions, exploring the notion of value in the Business Model approach.L'innovation technologique, qu'elle soit conduite par des start-ups ou par de grandes entreprises, n'est plus une condition suffisante de la création de valeur. Créer de la valeur sur des marchés nouveaux nécessite le plus souvent de repenser l'organisation de l'entreprise, sa façon de faire des affaires, ses partenariats stratégiques, autrement dit, son business model. Cet ouvrage se veut un guide pour les porteurs de projets d'innovation en leur fournissant des outils de compréhension et d'analyse de la dimension stratégique de leur projet. Les études de cas présentées sont le fruit d'une collaboration étroite entre les porteurs de chacun des projets et des chercheurs en management de l'innovation reconnus. Au travers de ces cas, trois grandes problématiques sont abordées : l'identification des sources de valeur chez les clients potentiels, la position que l'entreprise pourra prendre dans son écosystème et enfin l'évolution des business models dans le temps. Sur chacun des cas, le lecteur aura accès à une compréhension fine des problèmes stratégiques posés par l'innovation ainsi que des outils de management mis en œuvre pour aider à réfléchir et à agir. (http://www.rethinkingbusinessmodel.net/

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication