1,869 research outputs found
Analysis and classification of the breathing pattern in patients on weaning trial process
La estimación del momento óptimo de retirar la ventilación asistida de un paciente en cuidado intensivo sigue
siendo fundamental en la práctica clínica. En este trabajo se estudia el patrón respiratorio a partir de la señal de flujo respiratorio de
pacientes en proceso de extubación teniendo en cuenta las siguientes etapas: caracterización de la señal a partir de la identificación
de los ciclos respiratorios, análisis del patrón respiratorio a partir del modelado matemático de las series, y clasificación del mismo
con el objetivo de identificar patrones de pacientes con posible éxito en el proceso. Se analizaron 153 pacientes clasificados en
los grupos éxito, fracaso y reintubados, de acuerdo con el resultado de la prueba de extubación de tubo en T. Se seleccionaron las
series temporales de tiempo de espiración, tiempo de inspiración, duración del ciclo respiratorio e índice de respiración superficial
dado que presentaron diferencias significativas en los parámetros de valor medio, orden del modelo, primer coeficiente y error
final de predicción. Con ellas se obtuvo una exactitud de clasificación del 86% (sensibilidad 0,86 – especificidad 0,84) utilizando
un clasificador tipo discrimante lineal. Se analizaron otros clasificadores como regresión logística y máquinas de soporte vectorial.Estimating the optimal time to remove the ventilatory support from a patient in intensive care remains essential in
clinical practice. In this work we study the breathing pattern from the respiratory flow signal in the process of weaning considering
the following stages: characterization of the signal from the identification of respiratory cycles, respiratory pattern analysis from
mathematical modeling of the resulting series, and classification in order to identify patterns of patients with possible success
in the process. We analyzed 153 patients classified into three groups: success, failure and reintubated, according to results of
T-tube test. The time series for breathing duration, inspiratory time, expiratory time, and shallow breathing index that resulted in
significant differences in the mean, model order, first coefficient and final error of prediction were selected. With them we obtained
a classification accuracy of 86% (sensitivity 0.84 - specificity 0.86) using a linear classifier discriminate type. Other classifications
were analyzed, such as logistic regression and support vector machines
Scale-invariant magnetoresistance in a cuprate superconductor
The anomalous metallic state in high-temperature superconducting cuprates is
masked by the onset of superconductivity near a quantum critical point. Use of
high magnetic fields to suppress superconductivity has enabled a detailed study
of the ground state in these systems. Yet, the direct effect of strong magnetic
fields on the metallic behavior at low temperatures is poorly understood,
especially near critical doping, . Here we report a high-field
magnetoresistance study of thin films of \LSCO cuprates in close vicinity to
critical doping, . We find that the metallic state
exposed by suppressing superconductivity is characterized by a
magnetoresistance that is linear in magnetic field up to the highest measured
fields of T. The slope of the linear-in-field resistivity is
temperature-independent at very high fields. It mirrors the magnitude and
doping evolution of the linear-in-temperature resistivity that has been
ascribed to Planckian dissipation near a quantum critical point. This
establishes true scale-invariant conductivity as the signature of the strange
metal state in the high-temperature superconducting cuprates.Comment: 10 pages, 3 figure
Producción artesanal de semillas de Cratylia argentea cv. Veranera, accesiones CIAT 18516 y 18668
Discontinuous galerkin spectral/hp element modelling of dispersive shallow water systems
La Curva en S como Herramienta para la Medición de los Ciclos de Vida de Productos
The aim of this article was to carry out a study of the life cycles of three products of Colombian companies; based on a logistic model of population growth as a life cycles measurement tool. We found that the products life cycles have a similar behavior to the population growth, according to an S curve. The inflection points of the curves were obtained by a nonlinear regression. These points might be used as a tool for strategic decision making in products, in terms of identifying key instants for launching technological innovations, investments and execute marketing strategies
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