Curve Sign Inventorying Method Using Smartphones and Deep Learning Technologies

The objective of the proposed research is to develop and assess a system using smartphones and deep learning technologies to automatically establish an intelligent and sustainable curve sign inventory from videos. The Manual on the Uniform Traffic Control Devices (MUTCD) is the nationwide regulator that defines the standards used for transportation asset installation and maintenance. The proposed system is one of the components of a larger methodology whose purpose is to accomplish a frequent and cost-effective MUTCD curve sign compliance checking and other curve safety checking in order to reduce the number of deadly crashes on curves. To automatically build an effective sign inventory from videos, four modules are needed: sign detection, classification, tracking and localization. For this purpose, a pipeline has been developed in the past by former students of the Transportation laboratory of Georgia Tech. However, this pipeline is not accurate enough and its different modules have never been critically tested and assessed. Therefore, the objective of this study is to improve the different modules and particularly the detection module, which is the most important module of the pipeline, and to critically assess these improved modules to determine the pipeline ability to build an effective sign inventory. The proposed system has been tested and assessed in real conditions on a mountain road with many curves and curve signs; it has shown that the detection module is able to detect every single curve sign with a very low number of detected non-curve signs (false positive), resulting in a precision of 0.97 and a recall of 1. The other modules also showed very promising results. Overall, this study demonstrates that the proposed system is suitable for building an accurate curve sign inventory that can be used by transportation agencies to get a precise idea of the condition of the curve sign networks on a particular road.M.S

In search of the authentic nation: landscape and national identity in Canada and Switzerland

While the study of nationalism and national identity has flourished in the last decade, little attention has been devoted to the conditions under which natural environments acquire significance in definitions of nationhood. This article examines the identity-forming role of landscape depictions in two polyethnic nation-states: Canada and Switzerland. Two types of geographical national identity are identified. The first – what we call the ‘nationalisation of nature’– portrays zarticular landscapes as expressions of national authenticity. The second pattern – what we refer to as the ‘naturalisation of the nation’– rests upon a notion of geographical determinism that depicts specific landscapes as forces capable of determining national identity. The authors offer two reasons why the second pattern came to prevail in the cases under consideration: (1) the affinity between wild landscape and the Romantic ideal of pure, rugged nature, and (2) a divergence between the nationalist ideal of ethnic homogeneity and the polyethnic composition of the two societies under consideration

A statistical model for estimation of fish density including correlation in size, space, time and between species from research survey data

Trawl survey data with high spatial and seasonal coverage were analysed using a variant of the Log Gaussian Cox Process (LGCP) statistical model to estimate unbiased relative fish densities. The model estimates correlations between observations according to time, space, and fish size and includes zero observations and over-dispersion. The model utilises the fact the correlation between numbers of fish caught increases when the distance in space and time between the fish decreases, and the correlation between size groups in a haul increases when the difference in size decreases. Here the model is extended in two ways. Instead of assuming a natural scale size correlation, the model is further developed to allow for a transformed length scale. Furthermore, in the present application, the spatial- and size-dependent correlation between species was included. For cod (Gadus morhua) and whiting (Merlangius merlangus), a common structured size correlation was fitted, and a separable structure between the time and space-size correlation was found for each species, whereas more complex structures were required to describe the correlation between species (and space-size). The within-species time correlation is strong, whereas the correlations between the species are weaker over time but strong within the year

Cycling of lithogenic marine particles in the US GEOTRACES North Atlantic transect

© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Deep Sea Research Part II: Topical Studies in Oceanography 116 (2015): 283-302, doi:10.1016/j.dsr2.2014.11.019.In this paper, we present, describe, and model the first size-fractionated (0.8–51 µm; >51 µm) water-column particulate trace metal results from the US GEOTRACES North Atlantic Zonal Transect in situ pumping survey, with a focus on the lithogenic tracer elements Al, Fe and Ti. This examination of basin-wide, full-depth distributions of particulate elements elucidates many inputs and processes—some for bulk lithogenic material, others element-specific—which are presented via concentration distributions, elemental ratios, size-fractionation dynamics, and steady-state inventories. Key lithogenic inputs from African dust, North American boundary interactions, the Mediterranean outflow, hydrothermal systems, and benthic nepheloid layers are described. Using the refractory lithogenic tracer Ti, we develop a 1-D model for lithogenic particle distributions and test the sensitivities of size-fractionated open-ocean particulate Ti profiles to biotically driven aggregation, disaggregation rates, vertical sinking speeds, and dust input rates. We discuss applications of this lithogenic model to particle cycling in general, and to POC cycling specifically.International and US GEOTRACES Offices (OCE-0850963 and OCE-1129603), and fellowship assistance from the Williams College Tyng Fellowship and MIT/WHOI Academic Programs Office to DCO

Autoantibodies against type I IFNs in patients with life-threatening COVID-19

Interindividual clinical variability in the course of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is vast. We report that at least 101 of 987 patients with life-threatening coronavirus disease 2019 (COVID-19) pneumonia had neutralizing immunoglobulin G (IgG) autoantibodies (auto-Abs) against interferon-w (IFN-w) (13 patients), against the 13 types of IFN-a (36), or against both (52) at the onset of critical disease; a few also had auto-Abs against the other three type I IFNs. The auto-Abs neutralize the ability of the corresponding type I IFNs to block SARS-CoV-2 infection in vitro. These auto-Abs were not found in 663 individuals with asymptomatic or mild SARS-CoV-2 infection and were present in only 4 of 1227 healthy individuals. Patients with auto-Abs were aged 25 to 87 years and 95 of the 101 were men. A B cell autoimmune phenocopy of inborn errors of type I IFN immunity accounts for life-threatening COVID-19 pneumonia in at least 2.6% of women and 12.5% of men

Apport de la gravimetrie a la connaissance des structures geologiques profondes sous le bassin Aquitain : extension de la chaine hercynienne

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

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