Parametric information geometry with the package Geomstats

We introduce the information geometry module of the Python package Geomstats. The module first implements Fisher-Rao Riemannian manifolds of widely used parametric families of probability distributions, such as normal, gamma, beta, Dirichlet distributions, and more. The module further gives the Fisher-Rao Riemannian geometry of any parametric family of distributions of interest, given a parameterized probability density function as input. The implemented Riemannian geometry tools allow users to compare, average, interpolate between distributions inside a given family. Importantly, such capabilities open the door to statistics and machine learning on probability distributions. We present the object-oriented implementation of the module along with illustrative examples and show how it can be used to perform learning on manifolds of parametric probability distributions

Metagenome-based diversity analyses suggest a significant contribution of non-cyanobacterial lineages to carbonate precipitation in modern microbialites

Frontiers in Microbiology 6 (2015): 797 This Document is Protected by copyright and was first published by Frontiers. All rights reserved. It is reproduced with permissionCyanobacteria are thought to play a key role in carbonate formation due to their metabolic activity, but other organisms carrying out oxygenic photosynthesis (photosynthetic eukaryotes) or other metabolisms (e.g., anoxygenic photosynthesis, sulfate reduction), may also contribute to carbonate formation. To obtain more quantitative information than that provided by more classical PCR-dependent methods, we studied the microbial diversity of microbialites from the Alchichica crater lake (Mexico) by mining for 16S/18S rRNA genes in metagenomes obtained by direct sequencing of environmental DNA. We studied samples collected at the Western (AL-W) and Northern (AL-N) shores of the lake and, at the latter site, along a depth gradient (1, 5, 10, and 15 m depth). The associated microbial communities were mainly composed of bacteria, most of which seemed heterotrophic, whereas archaea were negligible. Eukaryotes composed a relatively minor fraction dominated by photosynthetic lineages, diatoms in AL-W, influenced by Si-rich seepage waters, and green algae in AL-N samples. Members of the Gammaproteobacteria and Alphaproteobacteria classes of Proteobacteria, Cyanobacteria, and Bacteroidetes were the most abundant bacterial taxa, followed by Planctomycetes, Deltaproteobacteria (Proteobacteria), Verrucomicrobia, Actinobacteria, Firmicutes, and Chloroflexi. Community composition varied among sites and with depth. Although cyanobacteria were the most important bacterial group contributing to the carbonate precipitation potential, photosynthetic eukaryotes, anoxygenic photosynthesizers and sulfate reducers were also very abundant. Cyanobacteria affiliated to Pleurocapsales largely increased with depth. Scanning electron microscopy (SEM) observations showed considerable areas of aragonite-encrusted Pleurocapsa-like cyanobacteria at microscale. Multivariate statistical analyses showed a strong positive correlation of Pleurocapsales and Chroococcales with aragonite formation at macroscale, and suggest a potential causal link. Despite the previous identification of intracellularly calcifying cyanobacteria in Alchichica microbialites, most carbonate precipitation seems extracellular in this systemWe are grateful to Eleonor Cortés for help and good company during the field trip and to Eberto Novelo for helpful discussions at the UNAM lab. This research was funded by the European Research Council Grants ProtistWorld (PI PL-G., Grant Agreement no. 322669) and CALCYAN (PI KB, Grant Agreement no. 307110) under the European Union’s Seventh Framework Program and the RTP Génomique environnementale of the CNRS (project MetaStrom, PI DM

Facilitating the design of human-centered and memorable travel experiences

In the fast-changing world with increasingly empowered customers, human-centricity and designing meaningful experiences have become crucial topics amongst businesses to stay relevant, attract customers and differentiate from others. The approach of putting customers at the centre, applying human-centered design and creating superior experiences are dominating the strategic discussions. However, studies show that a majority of businesses are struggling to operate in a customer-centric way. In small businesses, lack of resources and competences are often preventing to understand the needs and keep up with ever-changing aspirations and trends, and as a result, designing great customer experiences becomes challenging. The objective of this thesis is to explore how design thinking, service design and experience design can help small travel entrepreneurs to design more memorable experiences. The theoretical framework draws from the customer-dominant logic, design thinking and experience design. The methodological approach is qualitative, applying instrumental case study approach, and benefiting from the field of design thinking and service design. To understand the needs, challenges and opportunities of new travel entrepreneurs to design experiences, research data was gathered through desk research, content analysis, thematic interviews, observations and feedback collection during an on-site experience testing event, followed by a co-creation workshop and concepting. Three objectives were achieved in this design project. Firstly, new travel entrepreneurs gained knowledge on human-centric design from the travellers’ perspectives and built an understanding on the concept of defining moments and journeys and the significance of emotions to create memorable experiences. Secondly, this project showed the value of experience testing and co-creation to gain valuable feedback and customer insights to learn and iterate. Thirdly, it could be jointly concluded that for entrepreneurs it is a change journey to improve experiences by applying human-centric design. It requires a mindset shift and continuous learning to acquire relevant knowledge, skills and tools

Parametric information geometry with the package Geomstats

We introduce the information geometry module of the Python package Geomstats. The module first implements Fisher-Rao Riemannian manifolds of widely used parametric families of probability distributions, such as normal, gamma, beta, Dirichlet distributions, and more. The module further gives the Fisher-Rao Riemannian geometry of any parametric family of distributions of interest, given a parameterized probability density function as input. The implemented Riemannian geometry tools allow users to compare, average, interpolate between distributions inside a given family. Importantly, such capabilities open the door to statistics and machine learning on probability distributions. We present the object-oriented implementation of the module along with illustrative examples and show how it can be used to perform learning on manifolds of parametric probability distributions

Parametric information geometry with the package Geomstats

We introduce the information geometry module of the Python package Geomstats. The module first implements Fisher-Rao Riemannian manifolds of widely used parametric families of probability distributions, such as normal, gamma, beta, Dirichlet distributions, and more. The module further gives the Fisher-Rao Riemannian geometry of any parametric family of distributions of interest, given a parameterized probability density function as input. The implemented Riemannian geometry tools allow users to compare, average, interpolate between distributions inside a given family. Importantly, such capabilities open the door to statistics and machine learning on probability distributions. We present the object-oriented implementation of the module along with illustrative examples and show how it can be used to perform learning on manifolds of parametric probability distributions

Parametric information geometry with the package Geomstats

We introduce the information geometry module of the Python package Geomstats. The module first implements Fisher-Rao Riemannian manifolds of widely used parametric families of probability distributions, such as normal, gamma, beta, Dirichlet distributions, and more. The module further gives the Fisher-Rao Riemannian geometry of any parametric family of distributions of interest, given a parameterized probability density function as input. The implemented Riemannian geometry tools allow users to compare, average, interpolate between distributions inside a given family. Importantly, such capabilities open the door to statistics and machine learning on probability distributions. We present the object-oriented implementation of the module along with illustrative examples and show how it can be used to perform learning on manifolds of parametric probability distributions

WHO guidelines for antiretroviral therapy in serodiscordant couples in sub-Saharan Africa

International audienc

High prevalence of being Overweight and Obese HIV-infected persons, before and after 24 months on early ART in the ANRS 12136 Temprano Trial

International audienceAbstractBackgroundHIV is usually associated with weight loss. World health Organization (WHO) recommends early antiretroviral (ART) initiation, but data on the progression of body mass index (BMI) in participants initiating early ART in Africa are scarce.MethodsThe Temprano randomized trial was conducted in Abidjan to assess the effectiveness of early ART and Isoniazid (INH) prophylaxis for tuberculosis in HIV-infected persons with high CD4 counts below 800 cells/mm3 without any indication for starting ART. Patients initiating early ART before December 2010 were included in this sub-study. BMI was categorized as: underweight (<18.5 kg/m2), normal weight (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2) and obese (≥30 kg/m2). At baseline and after 24 months of ART, prevalence of being overweight or obese and factors associated with being overweight or obese were estimated using univariate and multivariate logistic regression.ResultsAt baseline, 755 participants (78 % women; median CD4 count 442/mm3, median baseline BMI 22 kg/m2) initiated ART. Among them, 19.7 % were overweight, and 7.2 % were obese at baseline. Factors associated with being overweight or obese were: female sex aOR 2.3 (95 % CI 1.4–3.7), age, aOR for 5 years 1.01 (95 % CI 1.0–1.2), high living conditions aOR 2.6 (95 % CI 1.5–4.4), High blood pressure aOR 4.3 (95 % CI 2.0–9.2), WHO stage 2vs1 aOR 0.7 (95 % CI 0.4–1.0) and Hemoglobin ≥95 g/dl aOR 3.0 (95 % CI 1.6–5.8). Among the 597 patients who attended the M24 visit, being overweight or obese increased from 20.4 to 24.8 % (p = 0.01) and 7.2 to 9.2 % (p = 0.03) respectively and factor associated with being overweight or obese was immunological response measured as an increase of CD4 cell count between M0–M24 (for +50 cells/mm3: aOR 1.01; 95 % CI 1.05–1.13, p = 0.01).ConclusionThe weight categories overweight and obese are highly prevalent in HIV-infected persons with high CD4 cell counts at baseline, and increased over 24 months on ART in this Sub-Saharan African population

Quantiferon-TB Gold: Performance for Ruling out Active Tuberculosis in HIV-Infected Adults with High CD4 Count in Côte d'Ivoire, West Africa

<div><p>Objective</p><p>To assess the performance of QuantiFERON-TB Gold In-Tube (QFT-GIT) test for active tuberculosis (TB) in HIV adults, and its variation over time in patients on antiretroviral therapy (ART) and/or isoniazide preventive therapy (IPT).</p><p>Methods</p><p>Transversal study and cohort nested in the Temprano ANRS 12136 randomized controlled trial assessing benefits of initiating ART earlier than currently recommended by World Health Organization, with or without a 6-month IPT. Performance of QFT-GIT for detecting active TB at baseline in the first 50% participants, and 12-month incidence of conversion/reversion in the first 25% participants were assessed. QFT-GIT threshold for positivity was 0.35 IU/ml.</p><p>Results</p><p>Among the 975 first participants (median baseline CD4 count 383/mm³, positive QFT-GIT test 35%), 2.7% had active TB at baseline. QFT-GIT sensitivity, specificity, positive and negative predictive value for active TB were 88.0%, 66.6%, 6.5% and 99.5%. For the 444 patients with a second test at 12 months, rates for conversion and reversion were 9.3% and 14%. Reversion was more frequent in patients without ART and younger patients. IPT and early ART were not associated with reversion/conversion.</p><p>Conclusion</p><p>A negative QFT-GIT could rule out active TB in HIV-infected adults not severely immunosuppressed, thus avoiding repeated TB testing and accelerating diagnosis and care for other diseases.</p><p>Trial Registration</p><p>ClinicalTrials.gov <a href="http://clinicaltrials.gov/ct2/results?term=NCT00495651" target="_blank">NCT00495651</a>.</p></div