Bayesian inference for the half-normal and half-t distributions

In this article we consider approaches to Bayesian inference for the half-normal and half-t distributions. We show that a generalized version of the normal-gamma distribution is conjugate to the half-normal likelihood and give the moments of this new distribution. The bias and coverage of the Bayesian posterior mean estimator of the halfnormal location parameter are compared with those of maximum likelihood based estimators. Inference for the half-t distribution is performed using Gibbs sampling and model comparison is carried out using Bayes factors. A real data example is presented which demonstrates the fitting of the half-normal and half-t models

BAYESIAN INFERENCE FOR THE HALF-NORMAL AND HALF-T DISTRIBUTIONS

In this article we consider approaches to Bayesian inference for the half-normal and half-t distributions. We show that a generalized version of the normal-gamma distribution is conjugate to the half-normal likelihood and give the moments of this new distribution. The bias and coverage of the Bayesian posterior mean estimator of the halfnormal location parameter are compared with those of maximum likelihood based estimators. Inference for the half-t distribution is performed using Gibbs sampling and model comparison is carried out using Bayes factors. A real data example is presented which demonstrates the fitting of the half-normal and half-t models.

Sidechain control of porosity closure in multiple peptide-based porous materials by cooperative folding

Porous materials find application in separation, storage and catalysis. We report a crystalline porous solid formed by coordination of metal centres with a glycylserine dipeptide. We prove experimentally that the structure evolves from a solvated porous into a non-porous state as result of ordered displacive and conformational changes of the peptide that suppress the void space in response to environmental pressure. This cooperative closure, which recalls the folding of proteins, retains order in three-dimensions and is driven by the hydroxyl groups acting as H-bond donors in the peptide sequence through the serine residue. This ordered closure is also displayed by multipeptide solid solutions in which the combination of different sequences of amino acids controls their guest response in a non-linear way. This functional control can be compared to the effect of single point mutations in proteins, where the exchange of single amino acids can radically alter structure and functio

Élargir les mandats de responsabilité sociale à la recherche biomédicale dans les facultés canadiennes

Background: Social accountability (SA), as defined by Boelen and Heck, is the obligation of medical schools to address the needs of communities through education, research and service activities. While SA is embedded within health profession education frameworks in medicine, they are rarely taught within graduate-level (MSc/PhD) education. Methods: As these programs train future medical researchers, we invited first-year graduate students enrolled in a mandatory professionalism class at our institution (n = 111) to complete a survey on their perceptions of the importance of SA in their research, training, and future careers. Results: Over 80% (n = 87) of respondents agreed that SA is relevant and felt committed to integrating it into their future research activities, only a limited number of students felt confident and/or supported in their abilities to integrate SA into their research. Conclusions: Specific SA training in graduate education is necessary for students to effectively incorporate elements of SA into their research, and as such support the SA mandates of their training institutions. We posit that awareness of SA principles formalizes the professional standards for biomedical researchers and is thus foundational for developing a professionalism curriculum in graduate education programs in medicine. We propose an expansion of the World Health Organization (WHO) partnership pentagon to include partners within the research ecosystem (funding partners, certification bodies) that collaborate with biomedical researchers to make research socially accountable.Contexte : La responsabilité sociale (RS), telle que définie par Boelen et Heck, est l'obligation pour les facultés de médecine de répondre aux besoins des communautés par l’entremise de l'éducation, de la recherche et des activités de service. Bien que la responsabilité sociale soit intégrée dans les cadres de formation des professionnels de santé en médecine, elle est rarement enseignée au niveau des études supérieures (MSc/PhD). Méthodes : Étant donné que ces programmes forment les futurs chercheurs médicaux, nous avons invité les étudiants de première année inscrits à un cours obligatoire sur le professionnalisme dans notre établissement (n = 111) à participer à une enquête sur leurs perceptions de l'importance de la RS dans leur recherche, leur formation et leur future carrière. Résultats : Plus de 80 % (n = 87) des répondants ont reconnu la pertinence de la RS et se sont engagés à l'intégrer dans leurs futures activités de recherche, mais seul un nombre limité d'étudiants se sont sentis confiants et/ou soutenus dans leurs capacités à intégrer la RS dans leur recherche. Conclusions : Une formation propre à la RS dans le cadre des études supérieures est nécessaire pour que les étudiants puissent intégrer efficacement des éléments de la RS dans leur recherche, et ainsi promouvoir les mandats de RS de leurs établissements de formation. Nous estimons que la sensibilisation aux principes de la RS formalise les normes professionnelles des chercheurs biomédicaux et qu'elle est donc fondamentale pour l'élaboration d'un programme de professionnalisme dans les programmes d'études supérieures en médecine. Nous proposons d'élargir le pentagone du partenariat de l'Organisation mondiale de la santé (OMS) pour y inclure les partenaires de l'écosystème de la recherche (partenaires financiers, organismes de certification) qui collaborent avec les chercheurs biomédicaux pour rendre la recherche socialement responsable

Initial experience of a large, self-expanding, and fully recapturable transcatheter aortic valve: The UK & Ireland Implanters' registry.

OBJECTIVES: The UK & Ireland Implanters' registry is a multicenter registry which reports on real-world experience with novel transcatheter heart valves. BACKGROUND: The 34 mm Evolut R transcatheter aortic valve is a self-expanding and fully recapturable transcatheter aortic valve, designed to treat patients with a large aortic annulus. METHODS: Between January 2017 and April 2018, clinical, procedural and 30-day outcome data were prospectively collected from all patients receiving the 34 mm Evolut R valve across 17 participating centers in the United Kingdom and Ireland. The primary efficacy outcome was the Valve Academic Research Consortium-2(VARC-2)-defined endpoint of device success. The primary safety outcome was the VARC-2-defined composite endpoint of early safety at 30 days. RESULTS: A total of 217 patients underwent attempted implant. Mean age was 79.5 ± 8.8 years and Society of Thoracic Surgeons Predicted Risk of Mortality Score 5.2% ± 3.4%. Iliofemoral access was used in 91.2% of patients. Device success was 79.7%. Mean gradient was 7.0 ± 4.6 mmHg and effective orifice area 2.0 ± 0.6 cm2 . Paravalvular regurgitation was more than mild in 7.2%. A new permanent pacemaker was implanted in 15.7%. Early safety was demonstrated in 91.2%. At 30 days, all-cause mortality was 3.2%, stroke 3.7%, and major vascular complication 2.3%. CONCLUSIONS: Real-world experience of the 34 mm Evolut R transcatheter aortic valve demonstrated acceptable procedural success, safety, valve function, and incidence of new permanent pacemaker implantation

Model selection in historical research using approximate Bayesian computation

Formal Models and History Computational models are increasingly being used to study historical dynamics. This new trend, which could be named Model-Based History, makes use of recently published datasets and innovative quantitative methods to improve our understanding of past societies based on their written sources. The extensive use of formal models allows historians to reevaluate hypotheses formulated decades ago and still subject to debate due to the lack of an adequate quantitative framework. The initiative has the potential to transform the discipline if it solves the challenges posed by the study of historical dynamics. These difficulties are based on the complexities of modelling social interaction, and the methodological issues raised by the evaluation of formal models against data with low sample size, high variance and strong fragmentation. This work examines an alternate approach to this evaluation based on a Bayesian-inspired model selection method. The validity of the classical Lanchester's laws of combat is examined against a dataset comprising over a thousand battles spanning 300 years. Four variations of the basic equations are discussed, including the three most common formulations (linear, squared, and logarithmic) and a new variant introducing fatigue. Approximate Bayesian Computation is then used to infer both parameter values and model selection via Bayes Factors. Results indicate decisive evidence favouring the new fatigue model. The interpretation of both parameter estimations and model selection provides new insights into the factors guiding the evolution of warfare. At a methodological level, the case study shows how model selection methods can be used to guide historical research through the comparison between existing hypotheses and empirical evidence.Funding for this work was provided by the SimulPast Consolider Ingenio project (CSD2010-00034) of the former Ministry for Science and Innovation of the Spanish Government and the European Research Council Advanced Grant EPNet (340828).Peer ReviewedPostprint (published version