Régie Autonome des Transports Parisiens (France)

The authors present an algorithm for determining the boundaries and profiles of snow avalanches’ paths, required to calculate their dynamic parameters. This data (release areas, inclination of release and transit zones), as well as resulting avalanches’ velocities and run-out distances, obtained through digital elevation models presented by various sources (ArcticDEM, ASTER GDEM, ALOS DEM, FABDEM), are compared with each other and DEM from laser scanning data as well as those constructed with the help of topographic maps and plans.The latter are traditionally used for statistical modeling of avalanche parameters in engineering surveys. The simulation results are verified by the data provided in the passports of the registered avalanche events. The tool for the ArcGIS GIS package was written in Python. The outcome is a text with the required characteristics, as well as a set of the avalanche paths’ individual components vector files. FABDEM was found to be the optimal digital model from the existing ones for such calculations. The best resolution of digital models was found to be 2,5–5 m

There are currently no neuroprotective drugs to delay or prevent appearance and progression of the HD symptoms and pathology. The disease involves complex pathogenic mechanisms but one of the earliest and most fundamental changes in the HD brain involves defects in vesicular trafficking that hinder the transport of Brain-Derived Neurotrophic Factor (BDNF) in the corticostriatal network, which is the most profoundly affected in HD. By combining selective proteomic analysis of vesicles transported within corticostriatal projecting neurons and in silico screening we identified palmitoylation as a pathway that could restore defective HTT-dependent trafficking within HD neurons. We showed that HX127, a specific inhibitor of the palmitate-removing enzyme APT1, restores axonal transport of BDNF and synapse homeostasis in HD neurons within a microfluidic network-on-a-chip, and in human HD iPSC-derived cortical neurons. We recently found that HX127 is also efficient at restoring mitochondrial activity that is impaired in HD neurons. HX127 is a brain-permeable small molecule which restored abnormally low levels of neuronal protein palmitoylation and rescued locomotor deficits and anxio-depressive behaviors in HD mice model. Further de-risking of HX127 revealed a good safety profile and demonstrated the absence of any long-term toxicity during 6-months treatment in vivo. We propose HX127 as a therapeutic compound of interest for HD since in contrast to current silencing approaches that are costly and invasive and have not yet proved to be beneficial to HD patients. HX127 is the first neuroprotective compound that acts on mutant HTT itself and restores its normal function.

Abstract T‐stubs and L‐stubs loaded in tension are generally assumed in contact with a rigid foundation. The prying force and stiffness of these components depend on this hypothesis. For double web angle riveted connections, the angle rests on deformable beam/column web. The objective of the present paper is to take into account the effects of this deformability on the development of the contact area, the rivet forces and the tensile stiffness. An enhanced theory of beam in contact with a tensionless Winkler foundation is adopted in the contact and lift‐off areas. The axial and bending flexibilities of rivets are also considered. A numerical analysis is also performed with ANSYS in order to validate the analytical model. A sensitivity study is conducted on the influence of the thickness of the horizontal leg. The analytical and the numerical results are in good agreement, which confirms the accuracy of the proposed mechanical model.

Underwater devices are critical for environmental applications. However, existing prototypes typically use bulky, noisy actuators and limited configurations. Consequently, they struggle to ensure noise-free and gentle interactions with underwater species when realizing practical functions. Therefore, we developed a jellyfish-like robotic platform enabled by a synergy of electrohydraulic actuators and a hybrid structure of rigid and soft components. Our 16-cm-diameter noise-free prototype could control the fluid flow to propel while manipulating objects to be kept beneath its body without physical contact, thereby enabling safer interactions. Its against-gravity speed was up to 6.1cm/s, substantially quicker than other examples in literature, while only requiring a low input power of around 100mW. Moreover, using the platform, we demonstrated contact-based object manipulation, fluidic mixing, shape adaptation, steering, wireless swimming, and cooperation of two to three robots. This study introduces a versatile jellyfish-like robotic platform with a wide range of functions for diverse applications.

ABSTRACT An analysis is presented to study the stability of a shallow masonry tunnel of the Paris metro subjected to the spreading of the vault’s supports caused by nearby excavations. FEM numerical computations are carried out using a specifically developed model for the masonry that combines a homogenization technique with a damage model. Calculations display three hinges in the vault. Measures show that the masonry vault may withstand about 2 centimeters of support spreading. Soil–structure interaction analysis shows that the ground reaction is critical to ensure stability. The loss of stiffness and shear strength of the soil next to the sidewalls produces severe deformations and cracks in the structure. Based on the results some thresholds are proposed. The study also presents an analysis on the importance of the constitutive law for masonry and a brief discussion on the use of Eurocodes to investigate the stability of the vault.

Mobility demand analysis is increasingly based on smart card data, that are generally aggregated into time series describing the volume of riders along time. These series present patterns resulting from multiple external factors. This paper investigates the problem of decomposing daily ridership data collected at a multimodal transportation hub. The analysis is based on structural time series models that decompose the series into unobserved components. The aim of the decomposition is to highlight the impact of long-term factors, such as trend or seasonality, and exogenous factors such as maintenance work or unanticipated events such as strikes or the COVID-19 health crisis. We focus our analysis on incoming flows of passengers to two transport lines known to be complementary in the Parisian public transport network. The available ridership data allows analysis over both long-term and short-term time horizons including significant events that have impacted people's mobility in the Paris region.