Efficiency in a forced contribution threshold public good game

We contrast and compare three ways of predicting efficiency in a forced contribution threshold public good game. The three alternatives are based on ordinal potential, quantal response and impulse balance theory. We report an experiment designed to test the respective predictions and find that impulse balance gives the best predictions. A simple expression detailing when enforced contributions result in high or low efficiency is provided

Full Agreement and the Provision of Threshold Public Goods

The experimental evidence suggests that groups are inefficient at providing threshold public goods. This inefficiency appears to reflect an inability to coordinate over how to distribute the cost of providing the good. So, why do groups not just split the cost equally? We offer an answer to this question by demonstrating that in a standard threshold public good game there is no collectively rational recommendation. We also demonstrate that if full agreement is required in order to provide the public good then there is a collectively rational recommendation, namely, to split the cost equally. Requiring full agreement may, therefore, increase efficiency in providing threshold public goods. We test this hypothesis experimentally and find support for it

Inside the “black box”: Embedding clinical knowledge in data-driven machine learning for heart disease diagnosis

Background: Ischemic heart disease (IHD) caused by the narrowing of coronary arteries is a major cause of morbidity and mortality worldwide. Clinical diagnosis involves complex, costly, and potentially invasive procedures. Objective: To address this problem, we introduce a novel clinical knowledge-enhanced machine learning (ML) pipeline to assist in timely and cost-effective IHD prediction. Methods: Unlike conventional data-driven “black box” ML approaches, we propose an effective mechanism to engage clinical expertise and gain insight into the “black box” at each stage of model development, including data analysis, preprocessing, selecting the most clinically discriminative features, and model evaluation. One-hot feature encoding is introduced to expose hidden bias and highlight the important elements and features. Results: Experimental results on the benchmark Cleveland IHD dataset showed that the proposed clinical knowledge–enhanced ML pipeline overperformed state-of-the-art data-driven ML models, using even fewer features. Our model based on one-hot feature encoding and support vector machine achieved the best accuracy of 94.4% and sensitivity 95% by using only 7 discriminative attributes. Conclusion: We share insights and discuss the effectiveness of incorporating clinical input in machine learning to improve model performance, as well as addressing some practical issues such as data bias and interpretability. We hope this preliminary study on engaging clinical expertise to explore the “black box” would improve the trustworthiness of AI and its potential wider uptake in the medical field

Les déchets ménagers dangereux : connaître les pratiques des usagers pour en améliorer la gestion

La Communauté Urbaine de Strasbourg (CUS) a mis en place un programme local de prévention des déchets ménagers afin d’atteindre l’objectif de réduction défini par la loi Grenelle. Son programme comprend 35 plans d’actions, dont un relatif à la réduction des déchets dangereux. Une filière de traitement spécifique existe pour ces déchets (apport en déchetterie). Pour en améliorer la connaissance et l’utilisation par les usagers (et dans le but de réduire les déchets de ce type), la CUS a défini des priorités en termes de sensibilisation aux produits dangereux et plus largement de promotions de techniques alternatives pour en réduire le nombre. Dans cette optique, et en partenariat avec la CUS, nous avons réalisé une enquête visant à connaitre les moyens d’action mobilisables pour mettre en place des actions répondant à ces priorités. L’enquête a été menée sous forme d’un questionnaire passé en face à face, auprès de la population de la CUS, durant la période du 2 au 10 février 2011. L’échantillon total compte 389 personnes, sélectionnées selon leur zone d’habitat, leur âge et leur catégorie CSP. Nous avons cherché à répondre à trois questions qui sont : 1.qu’est-ce qu’un déchet dangereux pour l’usager 2.comment l’usager gère ses déchets ménagers dangereux 3.comment l’usager explique son comportement face aux déchets ménagers dangereux. Les principaux résultats montrent que les usagers ne connaissent pas réellement les modalités spécifiques de traitement de ces déchets. Ils semblent néanmoins prêts à participer à leur réduction. Pour cela, et selon les enquêtés, l’amélioration de la gestion des déchets ménagers dangereux passe par : ­une meilleure information auprès des usagers ainsi qu’une politique éducative dans les milieux scolaires ; ­1. une réflexion sur la localisation et l’accessibilité des déchetteries spéciales ; ­2. une gestion moins « lourde » pour les usagers (proposition de collecte au porte à porte de la part des enquêtés)

IgG4-related periaortitis presenting as left flank pain

We present the case of periaortitis which presented initially with left flank pain. A diagnosis of IgG4-related disease (IgG4-RD) was subsequently made and managed as such. IgG4-RD is rare, can be difficult to diagnose, and requires clinical, serological, radiological and pathological correlation, particularly given that serum IgG4 levels may be normal. Immunosuppression is the mainstay treatment for this chronic condition alongside regular rheumatology input

An unusual cause of ventilatory failure in motor neurone disease

A patient previously diagnosed with motor neurone disease (MND) and gastrostomy-fed was under surveillance for ventilatory decline via our respiratory centre. At a planned review she was found to be hypercapnic, which would usually prompt an offer of non-invasive ventilation for home use. However, she was alkalotic and not acidotic as we might expect. Her serum potassium was checked urgently and confirmed as low. It was established that the community team had prescribed a feeding regime with insufficient potassium. Correction of hypokalaemia resolved her ventilatory failure. This case demonstrates the importance of co-ordinated care in the management of patients with MND