A Dynamic Screening Principle for the Lasso

International audienceThe Lasso is an optimization problem devoted to finding a sparse representation of some signal with respect to a predefined dictionary. An original and computationally-efficient method is proposed here to solve this problem, based on a dynamic screening principle. It makes it possible to accelerate a large class of optimization algorithms by iteratively reducing the size of the dictionary during the optimization process, discarding elements that are provably known not to belong to the solution of the Lasso. The iterative reduction of the dictionary is what we call dynamic screening. As this screening step is inexpensive, the computational cost of the algorithm using our dynamic screening strategy is lower than that of the base algorithm. Numerical experiments on synthetic and real data support the relevance of this approach

Fast Solving of the Group-Lasso via Dynamic Screening

International audienceWe propose to extend the dynamic screening principle, initially designed for the Lasso, to the Group-Lasso

Dynamic Screening: Accelerating First-Order Algorithms for the Lasso and Group-Lasso

Recent computational strategies based on screening tests have been proposed to accelerate algorithms addressing penalized sparse regression problems such as the Lasso. Such approaches build upon the idea that it is worth dedicating some small computational effort to locate inactive atoms and remove them from the dictionary in a preprocessing stage so that the regression algorithm working with a smaller dictionary will then converge faster to the solution of the initial problem. We believe that there is an even more efficient way to screen the dictionary and obtain a greater acceleration: inside each iteration of the regression algorithm, one may take advantage of the algorithm computations to obtain a new screening test for free with increasing screening effects along the iterations. The dictionary is henceforth dynamically screened instead of being screened statically, once and for all, before the first iteration. We formalize this dynamic screening principle in a general algorithmic scheme and apply it by embedding inside a number of first-order algorithms adapted existing screening tests to solve the Lasso or new screening tests to solve the Group-Lasso. Computational gains are assessed in a large set of experiments on synthetic data as well as real-world sounds and images. They show both the screening efficiency and the gain in terms running times

External validation of the Hospital Frailty Risk Score in France

BACKGROUND: The Hospital Frailty Risk Score (HFRS) has made it possible internationally to identify subgroups of patients with characteristics of frailty from routinely collected hospital data. OBJECTIVE: To externally validate the HFRS in France. DESIGN: A retrospective analysis of the French medical information database. SETTING: 743 hospitals in Metropolitan France. SUBJECTS: All patients aged 75 years or older hospitalised as an emergency in 2017 (n = 1,042,234). METHODS: The HFRS was calculated for each patient based on the index stay and hospitalisations over the preceding 2 years. Main outcome measures were 30-day in-patient mortality, length of stay (LOS) >10 days and 30-day readmissions. Mixed logistic regression models were used to investigate the association between outcomes and HFRS score. RESULTS: Patients with high HFRS risk were associated with increased risk of mortality and prolonged LOS (adjusted odds ratio [aOR] = 1.38 [1.35-1.42] and 3.27 [3.22-3.32], c-statistics = 0.676 and 0.684, respectively), while it appeared less predictive of readmissions (aOR = 1.00 [0.98-1.02], c-statistic = 0.600). Model calibration was excellent. Restricting the score to data prior to index admission reduced discrimination of HFRS substantially. CONCLUSIONS: HFRS can be used in France to determine risks of 30-day in-patient mortality and prolonged LOS, but not 30-day readmissions. Trial registration: Reference ID on clinicaltrials.gov: ID: NCT03905629

Propagación sonora del ruido vehicular en espacios urbanos abiertos

In carrying out studies of acoustic impact or noise mapping, the methods that can be applied to calculate the noise level generated by the road traffic have many points in common but differ in some important aspects. Essentially, they share the concept of considering the total flow of vehicles along a given road as a linear sound source and subdivide it into individual sources that can be treated as point sources. The sound level LAeq in a particular position of reception is given by the sum of the individual contributions, considering the corresponding attenuation that applies to the sound propagating from point to point. The segmentation of the linear source is one of the aspect in which two of the most publicized methods of calculation differ. In this work the results of prediction by applying the ISO 9613 model and the Harmonoise model are compared and contrasted with field measurements.En la realización de estudios de impacto acústico o de mapeo de ruidos, los métodos de ingeniería que pueden aplicarse para calcular el nivel sonoro generado por la circulación de tráfico rodado tienen muchos puntos en común, pero difieren en algunos aspectos importantes. Fundamentalmente, comparten el concepto de considerar al flujo total de vehículos en una dada vía de circulación como una fuente sonora lineal y de subdividirla en fuentes individuales, que pueden ser tratadas como fuentes puntuales. De esto resulta que el nivel sonoro, LAeq en una determinada posición de recepción, está dado por la suma de las contribuciones individuales, con la correspondiente atenuación que sufre el sonido al propagarse punto a punto, desde cada una de las fuentes hasta el receptor. En la segmentación de la fuente lineal, es en donde aparece uno de los aspectos en que difieren dos de los métodos de cálculo más divulgados. En este trabajo se comparan los resultados de predicción obtenidos aplicando el modelo de la ISO 9613 y el del Harmonoise y se contrastan, a su vez, con mediciones de campo

Seismic noise-based methods for soft-rock landslide characterization

International audienceIn order to better understand the mechanics and dynamic of landslides, it is of primary interest to image correctly their internal structure. Several active geophysical methods are able to provide the geometry of a given landslide, but were rarely applied in 3 dimensions in the past. The main disadvantages of methods like seismic reflection or electrical tomographies are that there are heavy to set up, require for some heavy processing tools to implement, and consequently are expensive and time consuming. Moreover, in the particular case of soft-rock landslides, their respective sensitivity and resolution are not always adequate to locate the potential slip surfaces. The passive methods, which require lighter instrumentation and easier processing tools, can represent an interesting alternative, particularly for difficult accessible landslides. Among them, the seismic noise based methods have shown increasing applications and developments, in particular for seismic hazard mapping in urban environment. In this paper, we present seismic noise investigations carried out on two different sites, a mudslide and a translational clayey landslide where independent measurements (geotechnical and geophysical tests) were performed earlier. Our investigations were composed of H/V measurements, which are fast and easy to perform in the field, in order to image shear wave contrasts (slip surfaces), and seismic noise array method, which is heavier to apply and interpret, but provides S-waves velocity profile versus depth. The comparisons between geophysical investigations and geotechnical information proved the applicability of such passive methods in 3D complexes, but also some limitations. Indeed interpretation of these measurements can be tricky in rough and non-homogeneous terrains

A Tale of Two Oxidation States: Bacterial Colonization of Arsenic-Rich Environments

Microbial biotransformations have a major impact on contamination by toxic elements, which threatens public health in developing and industrial countries. Finding a means of preserving natural environments—including ground and surface waters—from arsenic constitutes a major challenge facing modern society. Although this metalloid is ubiquitous on Earth, thus far no bacterium thriving in arsenic-contaminated environments has been fully characterized. In-depth exploration of the genome of the β-proteobacterium Herminiimonas arsenicoxydans with regard to physiology, genetics, and proteomics, revealed that it possesses heretofore unsuspected mechanisms for coping with arsenic. Aside from multiple biochemical processes such as arsenic oxidation, reduction, and efflux, H. arsenicoxydans also exhibits positive chemotaxis and motility towards arsenic and metalloid scavenging by exopolysaccharides. These observations demonstrate the existence of a novel strategy to efficiently colonize arsenic-rich environments, which extends beyond oxidoreduction reactions. Such a microbial mechanism of detoxification, which is possibly exploitable for bioremediation applications of contaminated sites, may have played a crucial role in the occupation of ancient ecological niches on earth

Multi-omics Reveals the Lifestyle of the Acidophilic, Mineral-Oxidizing Model Species Leptospirillum ferriphilumT.

Leptospirillum ferriphilum plays a major role in acidic, metal-rich environments, where it represents one of the most prevalent iron oxidizers. These milieus include acid rock and mine drainage as well as biomining operations. Despite its perceived importance, no complete genome sequence of the type strain of this model species is available, limiting the possibilities to investigate the strategies and adaptations that Leptospirillum ferriphilum DSM 14647T (here referred to as Leptospirillum ferriphilum T) applies to survive and compete in its niche. This study presents a complete, circular genome of Leptospirillum ferriphilum T obtained by PacBio single-molecule real-time (SMRT) long-read sequencing for use as a high-quality reference. Analysis of the functionally annotated genome, mRNA transcripts, and protein concentrations revealed a previously undiscovered nitrogenase cluster for atmospheric nitrogen fixation and elucidated metabolic systems taking part in energy conservation, carbon fixation, pH homeostasis, heavy metal tolerance, the oxidative stress response, chemotaxis and motility, quorum sensing, and biofilm formation. Additionally, mRNA transcript counts and protein concentrations were compared between cells grown in continuous culture using ferrous iron as the substrate and those grown in bioleaching cultures containing chalcopyrite (CuFeS2). Adaptations of Leptospirillum ferriphilum T to growth on chalcopyrite included the possibly enhanced production of reducing power, reduced carbon dioxide fixation, as well as elevated levels of RNA transcripts and proteins involved in heavy metal resistance, with special emphasis on copper efflux systems. Finally, the expression and translation of genes responsible for chemotaxis and motility were enhanced.IMPORTANCE Leptospirillum ferriphilum is one of the most important iron oxidizers in the context of acidic and metal-rich environments during moderately thermophilic biomining. A high-quality circular genome of Leptospirillum ferriphilum T coupled with functional omics data provides new insights into its metabolic properties, such as the novel identification of genes for atmospheric nitrogen fixation, and represents an essential step for further accurate proteomic and transcriptomic investigation of this acidophile model species in the future. Additionally, light is shed on adaptation strategies of Leptospirillum ferriphilum T for growth on the copper mineral chalcopyrite. These data can be applied to deepen our understanding and optimization of bioleaching and biooxidation, techniques that present sustainable and environmentally friendly alternatives to many traditional methods for metal extraction