Performing Deep Recurrent Double Q-Learning for Atari Games

International audienceCurrently, many applications in Machine Learning are based on define new models to extract more information about data, In this case Deep Reinforcement Learning with the most common application in video games like Atari, Mario, and others causes an impact in how to computers can learning by himself with only information called rewards obtained from any action. There is a lot of algorithms modeled and implemented based on Deep Recurrent Q-Learning proposed by DeepMind used in AlphaZero and Go. In this document, We proposed Deep Recurrent Double Q-Learning which is an implementation of Deep Reinforcement Learning using Double Q-Learning algorithms and Recurrent Networks like LSTM and DRQN

WSAM: Visual Explanations from Style Augmentation as Adversarial Attacker and Their Influence in Image Classification

Currently, style augmentation is capturing attention due to convolutional neural networks (CNN) being strongly biased toward recognizing textures rather than shapes. Most existing styling methods either perform a low-fidelity style transfer or a weak style representation in the embedding vector. This paper outlines a style augmentation algorithm using stochastic-based sampling with noise addition to improving randomization on a general linear transformation for style transfer. With our augmentation strategy, all models not only present incredible robustness against image stylizing but also outperform all previous methods and surpass the state-of-the-art performance for the STL-10 dataset. In addition, we present an analysis of the model interpretations under different style variations. At the same time, we compare comprehensive experiments demonstrating the performance when applied to deep neural architectures in training settings.Comment: 8 pages, 10 figure

Propuesta de un patrón de arquitecturas de software para la interoperabilidad en dispositivos en la capa al borde de un ecosistema IoT

En los últimos años el Internet de las cosas ha generado una disrupción en el ecosistema de soluciones para usuarios finales con aplicaciones en la salud, agroindustria, medio ambiente y otras soluciones heterogéneas. Cada una de estas tienen su propio formato para verbalizar los datos proporcionados por los diferentes servicios SOAP, RESTful, REST-LD en formato JSON o XML que pueden ser entendidos por personas. Estos dispositivos se denominan “heterogéneos” porque provienen de diferentes proveedores de manufactura, diferentes lenguajes de programación como C, C++, Lua, Python, JavaScript, etc. Este documento se enfoca sobre dispositivos restringidos, es decir, dispositivos con poca capacidad de procesamiento y memoria con diferentes cadenas de datos sensados. Esta investigación propone un patrón de arquitectura de software para la interoperabilidad entre los dispositivos al borde de un ecosistema IoT y entre ecosistemas entre sí.In recent years, the Internet of Things has generated a disruption in the solution ecosystem for end users with applications in health, agro-industry, environment and other heterogeneous solutions. Each of these solutions has its own format to verbalize the data provided by different web services, including SOAP, RESTful and REST-LD, in JSON or XML format, so that said data can be understood by people. These devices are called “heterogeneous” because they come from different manufacturers and use different programming languages such as C, C++, Lua, Python, Javascript, etc. This document focuses on constrained devices, that is, devices with little processing capacity and memory, and different chains of acquired data. This research proposes a software architecture pattern for interoperability between devices on the edge of an IoT ecosystem and between ecosystems

Global ecological predictors of the soil priming effect.

Identifying the global drivers of soil priming is essential to understanding C cycling in terrestrial ecosystems. We conducted a survey of soils across 86 globally-distributed locations, spanning a wide range of climates, biotic communities, and soil conditions, and evaluated the apparent soil priming effect using 13C-glucose labeling. Here we show that the magnitude of the positive apparent priming effect (increase in CO2 release through accelerated microbial biomass turnover) was negatively associated with SOC content and microbial respiration rates. Our statistical modeling suggests that apparent priming effects tend to be negative in more mesic sites associated with higher SOC contents. In contrast, a single-input of labile C causes positive apparent priming effects in more arid locations with low SOC contents. Our results provide solid evidence that SOC content plays a critical role in regulating apparent priming effects, with important implications for the improvement of C cycling models under global change scenarios

BioContainers: An open-source and community-driven framework for software standardization

Motivation BioContainers (biocontainers.pro) is an open-source and community-driven framework which provides platform independent executable environments for bioinformatics software. BioContainers allows labs of all sizes to easily install bioinformatics software, maintain multiple versions of the same software and combine tools into powerful analysis pipelines. BioContainers is based on popular open-source projects Docker and rkt frameworks, that allow software to be installed and executed under an isolated and controlled environment. Also, it provides infrastructure and basic guidelines to create, manage and distribute bioinformatics containers with a special focus on omics technologies. These containers can be integrated into more comprehensive bioinformatics pipelines and different architectures (local desktop, cloud environments or HPC clusters). Availability and Implementation The software is freely available at github.com/BioContainers/.publishedVersio

Risk factors for developing ventilator-associated lower respiratory tract infection in patients with severe COVID-19:a multinational, multicentre study, prospective, observational study

Around one-third of patients diagnosed with COVID-19 develop a severe illness that requires admission to the Intensive Care Unit (ICU). In clinical practice, clinicians have learned that patients admitted to the ICU due to severe COVID-19 frequently develop ventilator-associated lower respiratory tract infections (VA-LRTI). This study aims to describe the clinical characteristics, the factors associated with VA-LRTI, and its impact on clinical outcomes in patients with severe COVID-19. This was a multicentre, observational cohort study conducted in ten countries in Latin America and Europe. We included patients with confirmed rtPCR for SARS-CoV-2 requiring ICU admission and endotracheal intubation. Only patients with a microbiological and clinical diagnosis of VA-LRTI were included. Multivariate Logistic regression analyses and Random Forest were conducted to determine the risk factors for VA-LRTI and its clinical impact in patients with severe COVID-19. In our study cohort of 3287 patients, VA-LRTI was diagnosed in 28.8% [948/3287]. The cumulative incidence of ventilator-associated pneumonia (VAP) was 18.6% [610/3287], followed by ventilator-associated tracheobronchitis (VAT) 10.3% [338/3287]. A total of 1252 bacteria species were isolated. The most frequently isolated pathogens were Pseudomonas aeruginosa (21.2% [266/1252]), followed by Klebsiella pneumoniae (19.1% [239/1252]) and Staphylococcus aureus (15.5% [194/1,252]). The factors independently associated with the development of VA-LRTI were prolonged stay under invasive mechanical ventilation, AKI during ICU stay, and the number of comorbidities. Regarding the clinical impact of VA-LRTI, patients with VAP had an increased risk of hospital mortality (OR [95% CI] of 1.81 [1.40-2.34]), while VAT was not associated with increased hospital mortality (OR [95% CI] of 1.34 [0.98-1.83]). VA-LRTI, often with difficult-to-treat bacteria, is frequent in patients admitted to the ICU due to severe COVID-19 and is associated with worse clinical outcomes, including higher mortality. Identifying risk factors for VA-LRTI might allow the early patient diagnosis to improve clinical outcomes. Trial registration: This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable

Social and Structural Factors Associated with HIV Infection among Female Sex Workers Who Inject Drugs in the Mexico-US Border Region

BACKGROUND: FSWs who inject drugs (FSW-IDUs) can acquire HIV through high risk sexual and injection behaviors. We studied correlates of HIV infection among FSW-IDUs in northern Mexico, where sex work is quasi-legal and syringes can be legally obtained without a prescription. METHODS: FSW-IDUs>18 years old who reported injecting drugs and recent unprotected sex with clients in Tijuana and Ciudad Juarez underwent surveys and HIV/STI testing. Logistic regression identified correlates of HIV infection. RESULTS: Of 620 FSW-IDUs, prevalence of HIV, gonorrhea, Chlamydia, trichomonas, syphilis titers ≥1:8, or any of these infections was 5.3%, 4%, 13%, 35%, 10% and 72%, respectively. Compared to other FSW-IDUs, HIV-positive women were more likely to: have syphilis titers ≥1:8 (36% vs. 9%, p<0.001), often/always inject drugs with clients (55% vs. 32%, p = 0.01), and experience confiscation of syringes by police (49% vs. 28%, p = 0.02). Factors independently associated with HIV infection were syphilis titers ≥1:8, often/always injecting with clients and police confiscation of syringes. Women who obtained syringes from NEPs (needle exchange programs) within the last month had lower odds of HIV infection associated with active syphilis, but among non-NEP attenders, the odds of HIV infection associated with active syphilis was significantly elevated. CONCLUSIONS: Factors operating in both the micro-social environment (i.e., injecting drugs with clients) and policy environment (i.e., having syringes confiscated by police, attending NEPs) predominated as factors associated with risk of HIV infection, rather than individual-level risk behaviors. Interventions should target unjustified policing practices, clients' risk behaviors and HIV/STI prevention through NEPs