A data-driven-based methodology for SHM in reinforced concrete structures using embedded fiber optic sensors and pattern recognition techniques is presented. A prototype of a reinforced concrete structure was built and instrumented in a novel fashion with FBGs bonded directly to the reinforcing steel bars, which, in turn, were embedded into the concrete structure. The structure was dynamically loaded using a shaker. Superficial positive damages were induced using bonded thin steel plates. Data for pristine and damaged states were acquired. Classifiers based on Mahalanobis’ distance of the covariance data matrix were developed for both supervised and unsupervised pattern recognition with an accuracy of up to 98%. It was demonstrated that the proposed sensing scheme in conjunction with the developed supervised and unsupervised pattern recognition techniques allows the detection of slight stiffness changes promoted by damages, even when strains are very small and the changes of these associated with the damage occurrence may seem negligible.

Structural health monitoring (SHM) is a branch of structural engineering which seeks for the development of monitoring systems that provide relevant information of any alteration that may occur in an engineering structure. This work presents the implementation of an SHM methodology in a prototype structure made of reinforced concrete by using fiber Bragg gratings (FBGs), a type of fiber optic sensor capable of measuring strain and temperature changes due to external stimuli. The SHM system includes an interrogation device and signal processing algorithms which are intended to study the physical variations on the FBGs measurements in order to detect anomalies in the structure promoted by a damage occurrence. The structure prototype is a porticoed structure which contains 48 embedded sensors: 32 of them are destinated for the strain measurement and are located in both columns and beams of the structure, 16 are temperature sensors which have been embedded for thermal compensation. Strain datasets for both pristine and damaged conditions were obtained for the structure while it was excited with a mechanical shaker which induced dynamic loading conditions resembling earthquakes. By using classification algorithms based on pattern recognition, it is intended to process the datasets with the aim of reaching the first level of SHM in the structure (damage detection).

Introduction On January 30th of 2020, the WHO declared the COVID-19 outbreak a health emergency. In Colombia the first case was reported on March 6th of 2020. The disease has unfavorable outcomes and mortality in patients with high risk factors like solid-organ transplant recipients. In Colombia the data of the behavior disease in liver transplant patients are limited. Objectives To describe the prevalence, need of admission to hospital, complications and mortality of COVID-19 in liver transplant recipients. Methods A descriptive study of case series was performed from March 1st of 2020 to January 31 st of 2021 in liver transplant recipients at Fundación Cardioinfantil-IC in Bogotá, Colombia. An analysis of clinical variables, severity laboratories, imaging and clinical follow-up were performed. Qualitative variables were described in percentage and quantitative variables were applied to a normality test using Kolmogorov Smirnov and Shapiro Wilk and the results were expressed as medians and IRQ or means and SD. Results Out of 540 adults liver transplant recipients on Fundación Cardioinfantil-IC, 34 patients (6.2%) were diagnosed with Covid 19, median age 62 years (IQR: 26), 20 (58%) male, 13 (38.2%) were admitted to hospitalization, and 4 (11.7%) required ICU. More frequent symptoms were fever in 17/34 patients (50%), cough in 17/34 (50%) and dyspnea 10/34 (29.4%). Ten patients (29.4%) had pneumonia as radiographic findings. Four patients required mechanical ventilation. Complications like acute renal injury were found in 3 patients, 1 patient required renal replacement therapy and 1 patient had gastrointestinal bleeding. 3 patients died (8.8%) on average 14 days of hospital length in ICU. Conclusion Although the group of liver transplant patients is considered to be at high risk for unfavorable outcomes in SARS COV2 infection, the data on mortality and complications were similar to the few data described in the literature.

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