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Il y a quelques jours, Stephen Roach, économiste renommé, a publié un remarquable article d'opinion dans le "Financial Times". Il a esquissé un avenir de stagflation (faible croissance et de forte inflation) en raison de la fragilité croissante des chaînes et de la baisse de la demande des consommateurs que le confinement a imposée.Selon nous, Stephen Roach a fondamentalement tort. En substance, cet argument réitère la crainte de nombreux nouveaux économistes classiques qui s'inspirent de l'affirmation de Milton Friedman selon laquelle l'inflation est toujours un phénomène monétaire.

The increasing availability of large-scale global positioning system data stemming from in-vehicle-embedded terminal devices enables the design of methods deriving road network cartographic information from drivers' recorded traces. Some machine learning approaches have been proposed in the past to train automatic road network map inference, and recently this approach has been successfully extended to infer road attributes as well, such as speed limitation or number of lanes. In this paper, we address the problem of detecting traffic signals from a set of vehicle speed profiles, under a classification perspective. Each data instance is a speed versus distance plot depicting over a hundred profiles on a 100-m-long road span. We proposed three different ways of deriving features: The first one relies on the raw speed measurements; the second one uses image recognition techniques; and the third one is based on functional data analysis. We input them into most commonly used classification algorithms, and a comparative analysis demonstrated that a functional description of speed profiles with wavelet transforms seems to outperform the other approaches with most of the tested classifiers. It also highlighted that random forests yield an accurate detection of traffic signals, regardless of the chosen feature extraction method, while keeping a remarkably low confusion rate with stop signs.

Aim: This paper explores the real practices of users of a smart carpooling application that learns their mobility habits and predicts their future trips to propose relevant matches. Method: A combination of usage data and interviews analysis allows us to explore the commuter experience from registration to the first and the next shared rides. Findings: The results highlight the shortcomings associated with human factors in carpooling and with human-smart system interactions. They show that perceptions of practical constraints and poor counterparts are the major reasons for difficulty in incorporating carpooling into daily mobility. Psychosocial barriers take different forms at different steps of the carpooling experience (search for information or guarantees about other users, the necessity of conversing with others, much uncertainty about how to behave). The fact that the service is smart amplifies these problems and reduces the desire to carpool again because it creates new misunderstandings (i.e., the user does not understand what the system vs. the other users do) and discomfort in relation to other riders (no answer, too many refusals, necessity of refusing, negative carpool experience, or concern over proposing a bad carpool). Despite these difficulties, the users perceive carpooling as a good solution and a positive human experience when the matching is accurate. We propose some recommendations to overcome the identified difficulties.

BACKGROUND: The exposome is defined as the totality of environmental exposures from conception onwards. It calls for providing a holistic view of environmental exposures and their effects on human health by evaluating multiple environmental exposures simultaneously during critical periods of life. OBJECTIVE: We evaluated the association of the urban exposome with birth weight. METHODS: We estimated exposure to the urban exposome, including the built environment, air pollution, road traffic noise, meteorology, natural space, and road traffic (corresponding to 24 environmental indicators and 60 exposures) for nearly 32,000 pregnant women from six European birth cohorts. To evaluate associations with either continuous birth weight or term low birth weight (TLBW) risk, we primarily relied on the DeletionSubstitution-Addition (DSA) algorithm, which is an extension of the stepwise variable selection method. Second, we used an exposure-byexposure exposome-wide association studies (ExWAS) method accounting for multiple hypotheses testing to report associations not adjusted for coexposures. RESULTS: The most consistent statistically significant associations were observed between increasing green space exposure estimated as Normalized Difference Vegetation Index (NDVI) and increased birth weight and decreased TLBW risk. Furthermore, we observed statistically significant associations among presence of public bus line, land use Shannon's Evenness Index, and traffic density and birth weight in our DSA analysis. CONCLUSION: This investigation is the first large urban exposome study of birth weight that tests many environmental urban exposures. It confirmed previously reported associations for NDVI and generated new hypotheses for a number of built-environment exposures.

Présentation du projet NoiseCapture dans le cadre du séminaire Immersion Sciences 2018, organisé conjointement par l’Académiede Rennes, la région Bretagne et le CNRS.

On-demand Ride-Hailing services (RHs) now play an increasing role within many cities around the world. RHs might increase traffic congestion, vehicle ownership and access inequalities. RHs pose significant challenges for policymakers, and addressing these issues requires detailed information about RHs use. But research on RHs services, especially in African cities, remains scarce. In this respect, this research presents original data on the use and users of RHs in Kenya’s capital, Nairobi, based on the results of an ad hoc survey designed by the author. This paper provides insights into who the users of RHs are, and their motivations for using RHs. Results show that RHs are extensively used in Nairobi (across all socio-economic groups, on a regular basis and way more for work-related trips than in many Western countries). In Nairobi, where only a minority of urban dweller have access to an individual motorized mode of transport, using RHs is gradually becoming necessary to access urban amenities. Nairobi’s inhabitants are facing a growing RHs dependency, which calls in return to public regulation.

This contribution is based on the European collaborative project TRANSFORMERS (Configurable and adaptable trucks and trailers for optimal transport), which received co-funding from the European Commission. The project has the goal of reducing energy use per tonne.kilometre of goods transported by up to 25%. This is achieved by innovations including: i) Configurable whole vehicle aerodynamics, ii) Improved loading efficiency measures, iii) A distributed, trailer mounted electric driveline known as ""hybrid-on-demand"" for truck-semitrailer combinations. The combination of innovations gives the possibility of a semi-trailer combination which can be adapted or re-configured to suit individual transport missions. The paper focuses on providing background to the project, an overview of the innovations developed within the project, and the main conclusions that were drawn from the wide range of work undertaken within the project. It covers both the ""Energy Efficiency"" and the ""Load Optimisation"" trailers which were developed and tested within the project.

_; This proposal adopts a holistic approach to strategic transport investment by discussing the wider economic impacts (WEIs) analysis method in terms of several dominant and emerging methods. The WEIs analysis goes beyond the effects captured in a standard cost-benefit analysis (CBA). A CBA addresses the market for transport services and infrastructure access but neglects the wider impacts on other markets. These wider impacts usually relate to agglomeration, market power, and the behavioral adaptions of firms and households. The high uncertainty in land use changes indicates that WEIs tend to occur in different forms on multiple spatial scales, varying by place and time. Additionally, some activities, such as education, have no direct market value, but may indirectly contribute to the overall economic output and human capital development in cities and regions. Given that the conventional elasticity methods are not goal oriented, it is important to ensure that the WEIs analysis accounts for the stakeholder-specific costs and benefits. Assuming that it is possible to consider all WEIs through theoretical models, major efforts should focus on establishing and maintaining appropriate methodologies and tools. The social and environmental data needed to address biodiversity issues should also be improved and promoted. Complementary to the WEIs, understanding how the behavior of agents changes in response to the new transport options will help clarify the long-term implications of transportation. This will suggest new strategies (territorial appropriation), approaches/ techniques to feasibility, and ?place-based? interrelations, that is, specific interrelations in places. This last aspect is especially important in the current context of the COVID-19 pandemic, which has affected and will likely change transportation behaviors and transport demand in the dynamic future.

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The interest in the elastic and yielding properties of fresh cement-based materials has recently grown due to the development of new processing techniques, which avoid the use of standard formworks. Without support, the material shaping relies only on the mechanical properties of the fresh material. Within this frame, the point of this paper is to gather the accepted knowledge along with the most recent advances on both yield stress and elasticity of fresh cement-based materials. In the first part, we will go through the physical and chemical origin of these macroscopic properties and their evolutions. In the second part, we will describe the way they can be measured while the third part will deal with the way they can be controlled and tuned. Finally, the most recent models for both properties prediction from mix design and processing modeling from rheological measurements will be described.