Diseño de la cimentación de Torre Reforma, México D.F.

El proyecto tiene como objetivo realizar el diseño de la cimentación de Torre Reforma. Torre Reforma se ubica en Av. Paseo de la Reforma No. 483, en la esquina con Rio Elba, en la ciudad de México. Dicha ubicación geotécnicamente corresponde a lo que se conoce como la Zona de Lago. La superficie construida será de 2780 m2 y el edificio contará con una altura de 244 m y un total de 57 plantas. Por debajo del nivel de calle el edificio constará de 10 niveles de sótano destinados a aparcamiento. Partiendo de los parámetros geotécnicos del terreno, el proyecto consistirá en calcular una parte de la cimentación empleada en este edificio. Este proyecto se podrá utilizar como guía para realizar cimentaciones parecidas para otros edificios. ABSTRACT The objective of this Project is to make the design of the foundation of Torre Reforma. Torre Reforma is located in Av. Paseo de la Reforma No. 483, on the corner with Río Elba in México City. Geotechnically this location corresponds to what it is known as “la Zona del Lago” or Lake Zone. The constructed area is of 2780 m2 and the building will have a height of 244 m and a total of 57 floors. Below street level the building will include ten basement levels for parking. Based on the geotechnical parameters of the site, the project will consist in calculating a part of the foundation used in this building. This project will be able to be used as a guide for future projects of foundations of buildings in similar conditions

LEA: Improving Sentence Similarity Robustness to Typos Using Lexical Attention Bias

Textual noise, such as typos or abbreviations, is a well-known issue that penalizes vanilla Transformers for most downstream tasks. We show that this is also the case for sentence similarity, a fundamental task in multiple domains, e.g. matching, retrieval or paraphrasing. Sentence similarity can be approached using cross-encoders, where the two sentences are concatenated in the input allowing the model to exploit the inter-relations between them. Previous works addressing the noise issue mainly rely on data augmentation strategies, showing improved robustness when dealing with corrupted samples that are similar to the ones used for training. However, all these methods still suffer from the token distribution shift induced by typos. In this work, we propose to tackle textual noise by equipping cross-encoders with a novel LExical-aware Attention module (LEA) that incorporates lexical similarities between words in both sentences. By using raw text similarities, our approach avoids the tokenization shift problem obtaining improved robustness. We demonstrate that the attention bias introduced by LEA helps cross-encoders to tackle complex scenarios with textual noise, specially in domains with short-text descriptions and limited context. Experiments using three popular Transformer encoders in five e-commerce datasets for product matching show that LEA consistently boosts performance under the presence of noise, while remaining competitive on the original (clean) splits. We also evaluate our approach in two datasets for textual entailment and paraphrasing showing that LEA is robust to typos in domains with longer sentences and more natural context. Additionally, we thoroughly analyze several design choices in our approach, providing insights about the impact of the decisions made and fostering future research in cross-encoders dealing with typos.Comment: KDD'23 conference (main research track). (*) These authors contributed equall

Nanofiltration of glucose: Analysis of parameters and membrane characterization

Membrane characterization and modeling of nanofiltration processes of uncharged solutes are of special interest for the food industry. In this work two commercial membranes, DK and DL, were used to concentrate glucose solutions. Membranes were characterized according hydrophobicity, thickness, porosity, and hydraulic permeability. The influence of pressure and concentration of glucose on the permeate flux and rejection were studied. Both membranes presented a great potential for the food industry due to their high rejection of glucose. The osmotic pressure model was combined with film theory and the real driven force was calculated taking into account the osmotic pressure and the concentration polarization. Both phenomena influenced the process (concentration polarization only in the most dilute solutions at low pressure) and the permeability for glucose solutions was similar to the hydraulic permeability. A mathematical model based on the Donnan-Steric Pore Model was used to determine the pore radius and the effective thickness of both membranes. As the concentration inside the pore (needed for the calculations) is difficult to measure experimentally, various alternatives were proposed. The average of the concentration at the interface and permeate best fitted the experimental data. The model was applied successfully; the maximum error was 8% within the range of concentrations (5–100 g/L) for the DL membrane and 5% for the DK membrane up to 50 g/L.Fil: Almazán, Jorge Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones Para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones Para la Industria Química; ArgentinaFil: Romero Dondiz, Estela María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones Para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones Para la Industria Química; ArgentinaFil: Rajal, Verónica Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones Para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones Para la Industria Química; ArgentinaFil: Castro Vidaurre, Elza Fani. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones Para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones Para la Industria Química; Argentin

Oxygen: From Toxic Waste to Optimal (Toxic) Fuel of Life

Some 2.5 billion years ago, the great oxygenation event (GOE) led to a 105‐fold rise in atmospheric oxygen [O2], killing most species on Earth. In spite of the tendency to produce toxic reactive oxygen species (ROS), the highly exergonic reduction of O2 made it the ideal biological electron acceptor. During aerobic metabolism, O2 is reduced to water liberating energy, which is coupled to adenosine triphosphate (ATP) synthesis. Today, all organisms either aerobic or not need to deal with O2 toxicity. O2‐permeant organisms need to seek adequate [O2], for example, aquatic crustaceans bury themselves in the sea bottom where O2 is scarce. Also, the intestinal lumen and cytoplasm of eukaryotes is a microaerobic environment where many facultative bacteria or intracellular symbionts hide from oxygen. Organisms such as plants, fish, reptiles and mammals developed O2‐impermeable epithelia, plus specialized external respiratory systems in combination with O2‐binding proteins such as hemoglobin or leg‐hemoglobin control [O2] in tissues. Inside the cell, ROS production is prevented by rapid O2 consumption during the oxidative phosphorylation (OxPhos) of ATP. When ATP is in excess, OxPhos becomes uncoupled in an effort to continue eliminating O2. Branched respiratory chains, unspecific pores and uncoupling proteins (UCPs) uncouple OxPhos. One last line of resistance against ROS is deactivation by enzymes such as super oxide dismutase and catalase. Aerobic organisms profit from the high energy released by the reduction of O2, while at the same time they need to avoid the toxicity of ROS

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group