Generating Subsurface Earth Models using Discrete Representation Learning and Deep Autoregressive Network

Subsurface earth models (referred to as geo-models) are crucial for characterizing complex subsurface systems. Multiple-point statistics are commonly used to generate geo-models. In this paper, a deep-learning-based generative method is developed as an alternative to the traditional Geomodel generation procedure. The generative method comprises two deep-learning models, namely the hierarchical vector-quantized variational autoencoder (VQ-VAE-2) and PixelSNAIL autoregressive model. Based on the principle of neural discrete representation learning, the VQ-VAE-2 learns to massively compress the Geomodels to extract the low-dimensional, discrete latent representation corresponding to each Geomodel. Following that, PixelSNAIL uses the deep autoregressive network to learn the prior distribution of the latent codes. For the purpose of Geomodel generation, PixelSNAIL samples from the newly learned prior distribution of latent codes, and then the decoder of the VQ-VAE-2 converts the newly sampled latent code to a newly constructed geo-model. PixelSNAIL can be used for unconditional or conditional geo-model generation. In an unconditional generation, the generative workflow generates an ensemble of geo-models without any constraint. On the other hand, in the conditional geo-model generation, the generative workflow generates an ensemble of geo-models similar to a user-defined source image, which ultimately facilitates the control and manipulation of the generated geo-models. To better construct the fluvial channels in the geo-models, the perceptual loss is implemented in the VQ-VAE-2 model instead of the traditional mean squared error loss. At a specific compression ratio, the quality of multi-attribute geo-model generation is better than that of single-attribute geo-model generation

Enantioselective PCCP Brønsted acid-catalyzed aza-Piancatelli rearrangement.

An enantioselective aza-Piancatelli rearrangement has been developed using a chiral Brønsted acid based on pentacarboxycyclopentadiene (PCCP). This reaction provides rapid access to valuable chiral 4-amino-2-cyclopentenone building blocks from readily available starting material and is operationally simple

Modelo arquitectónico desde la vista de información para apoyar la interoperabilidad de herramientas software que soportan la mejora de procesos de software

(Eng) Diverse software tools that support the software process improvement (SPI) not interoperate between them, that is to say, the exchange of information between the different tools is deficient, making it difficult to sequence and automatic re-use of information of SPI initiatives. In this article we present an architectural model from the information view to support the interoperability of software tools that support the stages of diagnosing the process and formulating improvements. The model establishes architecture that describes the type of information that can be exchanged these tools, as well as the structure of the data, their possible values, its semantics, and the restrictions imposed on the use and interpretation of such information. The architectural model is composed of a set of schemas, raised in conceptual form, which can be used by organizations that wish to develop software tools to interoperate, which provide support in a comprehensive way to diagnosing the process and formulating improvements of the SPI cycle. These schemas were evaluated using the qualitative method Focus Group.(Spa) La gran mayoría de herramientas software que soportan la mejora de procesos de software (SPI) no interoperan entre ellas, es decir, el intercambio de información entre las diferentes herramientas es deficiente, lo que dificulta la secuencia y reutilización automática de la información de las iniciativas de SPI. En este artículo presentamos un modelo arquitectónico desde la vista de información para apoyar la interoperabilidad de las herramientas software que soportan las etapas de Diagnóstico de procesos y Formulación de mejoras. El modelo establece la arquitectura que describe el tipo de información que pueden intercambiar estas herramientas, así como la estructura de los datos, sus posibles valores, su semántica, y las restricciones impuestas sobre la utilización e interpretación de dicha información. El modelo arquitectónico está constituido por un conjunto de esquemas planteados de forma conceptual, el cual puede ser utilizado por organizaciones que deseen desarrollar herramientas software que interoperen entre sí, las cuales brinden soporte de manera integral al Diagnóstico y Formulación del ciclo de SPI. Estos esquemas fueron evaluados utilizando el método cualitativo Focus Group

Reply to G. Betts's letter referring to "Serum potassium dynamics during acute heart failure hospitalization".

This work was funded by the Instituto de Salud Carlos III (Ministry of Economy, Industry and Competitiveness) and cofunded by the European Regional Development Fund, through the CIBER in cardiovascular diseases (CB16/11/00502).S

A Fine Grain Sentiment Analysis with Semantics in Tweets

Social networking is nowadays a major source of new information in the world. Microblogging sites like Twitter have millions of active users (320 million active users on Twitter on the 30th September 2015) who share their opinions in real time, generating huge amounts of data. These data are, in most cases, available to any network user. The opinions of Twitter users have become something that companies and other organisations study to see whether or not their users like the products or services they offer. One way to assess opinions on Twitter is classifying the sentiment of the tweets as positive or negative. However, this process is usually done at a coarse grain level and the tweets are classified as positive or negative. However, tweets can be partially positive and negative at the same time, referring to different entities. As a result, general approaches usually classify these tweets as “neutral”. In this paper, we propose a semantic analysis of tweets, using Natural Language Processing to classify the sentiment with regards to the entities mentioned in each tweet. We offer a combination of Big Data tools (under the Apache Hadoop framework) and sentiment analysis using RDF graphs supporting the study of the tweet’s lexicon. This work has been empirically validated using a sporting event, the 2014 Phillips 66 Big 12 Men’s Basketball Championship. The experimental results show a clear correlation between the predicted sentiments with specific events during the championship

Unconventional pseudostatic stability analysis of the Diezma landslide (Granada, Spain) based on a high-resolution engineering-geological model

A novel unconventional pseudostatic analysis is proposed here to infer on the sensitivity of a landslide to earthquakes characterized by different physical properties. Several sine waves with different amplitudes, frequencies and phases were applied to the landslide mass assuming limit equilibrium conditions. The unconventional approach was used for the Diezma landslide case study. The landslide is located 25 km from the city of Granada (Spain). Although the slope had repeatedly suffered small-scale stability problems since the construction of the A-92 highway, a larger failure occurred on 18 March 2001 and damaged the highway between kilometers 272.6 and 272.8. The landslide had an estimated volume of 1.2 Mm3 and involved a disordered deposit of silt and clay with heterometric blocks within the Numidoide Formation, which outcrops along the contact between the Maláguide and Dorsal domains of the Betic Cordillera mountain range. Despite the 18 million Euros spent since 1999 on geotechnical investigations and stabilization solutions, the numerous reactivations that occurred through 2010 and 2013 demonstrate the persistent activity of the landslide. The geometry of the large slope failure corresponding to the first activation of the Diezma landslide was used to back-analyze the stability of the slope based on a high-resolution engineering-geological model. The model was developed from the analysis of numerous borehole logs as well as from geophysical investigations consisting of seismic noise measurements. The results demonstrate that the safety factor (SF) of the Diezma landslide varies significantly for frequencies less than 1 Hz; moreover, unstable conditions are reached at frequency values between 0.5 and 1 Hz for water pressure distributions corresponding to Bishop factors (ru) between 0 and 0.36. To estimate the co-seismic displacements, the geometrical and mechanical properties of the landslide mass were used to derive its characteristic periods for thickness (Ts) and length (Tl), which were compared with the characteristic period of the earthquake (Tm). The results indicate that the maximum expected co-seismic displacements are up to 2 m for an earthquake with a Tm value close to 1 s and an Arias Intensity on the order of 1 m/s

A Repository of Semantic Open EHR Archetypes

This paper describes a repository of openEHR archetypes that have been translated to OWL. In the work presented here, five different CKMs (Clinical Knowledge Managers) have been downloaded and the archetypes have been translated to OWL. This translation is based on an existing translator that has been improved to solve programming problems with certain structures. As part of the repository a tool has been developed to keep it always up-to-date. So, any change in one of the CKMs (addition, elimination or even change of an archetype) will involve translating the changed archetypes once more. The repository is accessible through a Web interface (http://www.openehr.es/)

Influence of the electric field on the latent heat of the ferroelectric phase transition in KDP

The specific heat, heat flux (DTA trace) and dielectric constant of KDP ferroelectric crystal have been measured simultaneously for various electric fields with a conduction calorimeter. The specific heat presents a strong anomaly but these simultaneous measurements allow us to evaluate the latent heat accurately. Latent heat decreases with field and the value of critical electric field --that where latent heat disappears-- is estimated to be (0.44\pm0.03) kV/cm. Incidentally, we have measured simultaneously the dielectric permittivity which suggests that latent heat is developed as domains are growing.Comment: 7 pages, 6 figures, ReVTeX, twocolumn format, to appear in J. Phys. Cond. Matte

Squamous cell carcinoma related with dental implants. A clinical cases report

One third of all cases of head and neck carcinoma (CA) concern the oral mucosa. The use of dental implants (DI) for dental rehabilitation is widely extended. However, a few studies have reported some cases with neoplasic alterations, among the tissue surrounding implants. Our aim was to analyze possible alterations at the bone-implant interface in patients with oral squamous cell carcinoma (SCC), providing new evidence that could relate or discard a possible link between these factors. We used, for the first time, different techniques, including electron microscopy and histology, to analyze the implant ´s surface and the surrounding tissue from four clinical cases with neoplasic alterations surrounding DI. Histologically, ample inflammatory tissue was found in direct contact with the implant surface. Surface analysis of this tissue, revealed titanium percentages. According to our study, no oncological relation with deterioration of the implant surface was found, although DI were constantly related with peri-implantitis, a chronic trauma of the oral mucosa that could involve a neoplastic factor

Why the US spends more treating high-need high-cost patients: a comparative study of pricing and utilization of care in six high-income countries.

One of the most pressing challenges facing most health care systems is rising costs. As the population ages and the demand for health care services grows, there is a growing need to understand the drivers of these costs across systems. This paper attempts to address this gap by examining utilization and spending of the course of a year for two specific high-need high-cost patient types: a frail older person with a hip fracture and an older person with congestive heart failure and diabetes. Data on utilization and expenditure is collected across five health care settings (hospital, post-acute rehabilitation, primary care, outpatient specialty and drugs), in six countries (Canada (Ontario), France, Germany, Spain (Aragon), Sweden and the United States (fee for service Medicare) and used to construct treatment episode Purchasing Power Parities (PPPs) that compare prices using baskets of goods from the different care settings. The treatment episode PPPs suggest other countries have more similar volumes of care to the US as compared to other standardization approaches, suggesting that US prices account for more of the differential in US health care expenditures. The US also differs with regards to the share of expenditures across care settings, with post-acute rehab and outpatient speciality expenditures accounting for a larger share of the total relative to comparators