Introducción: Zika es una enfermedad ocasionada por infección con el virus Zika, un flavivirus de la familia Flaviviridae, transmitido por la picadura de mosquitos hembra Aedes aegypti o Aedes albopictus Objetivos: describir las características demográficas y sociales de los casos de Zika en la población urbana del municipio de Girardot, estimar el subregistro de casos de Zika no consultantes, estimar el subregistro de casos no notificados de Zika que asistieron a consulta diagnosticados como Zika en las instituciones prestadoras de servicios de salud de Girardot y no notificados, estimar el subregistro de casos que asistieron a consulta en las Instituciones prestadoras de servicios de salud de Girardot y no fueron diagnosticados, describir las causas del subregistro estimado, estimar la población infectada por Zika en Girardot. Metodología: se hizo un estudio descriptivo retrospectivo; la población en estudio fue la población urbana del municipio de Girardot. Se hizo un muestreo aleatorio simple con el total de las manzanas identificadas en el área urbana, con un intervalo de confianza del 95 %, un error aceptado del 5% y una probabilidad del 1,1 %; se obtuvo una muestra de 211 manzanas para realizar la encuesta de la búsqueda activa comunitaria; se hizo búsqueda activa comunitaria y búsqueda activa institucional en las IPS. Resultados: se encuestaron 3 502 viviendas en las que se registraron 5 542 personas; la tasa de ataque registrada en la búsqueda activa comunitaria fue del 15,2 %; el sexo masculino aportó el 59,9 % de los casos; el 49,1 % de los casos registrados en la búsqueda activa comunitaria no consultaron principalmente por automedicación. En la búsqueda activa institucional, en los pacientes que consultaron y se les hizo diagnóstico principal CIE-10 A929 y A928 (Zika), no fueron notificados al Sivigila el 81,7 %; en los pacientes que consultaron y se les hizo otros diagnósticos que nos pueden llevar a cumplir definición de caso de Zika, no fueron notificados al Sivigila el 94,4 %; con los datos de las dos búsquedas activas, en Girardot la transmisión se inició la semana 41 del 2015. Conclusiones: los casos no notificados a nivel institucional con diagnóstico A928 y A929 (Zika) fueron el 81,7 %, los casos no notificados a nivel institucional con otros diagnósticos que nos pueden hacer cumplirla definición de caso para Zika fueron el 94,4 %.
The hypothesis that the standardized ileal digestibility (SID) of AA, concentration of ME, and the standardized total tract digestibility (STTD) of P in an enhanced torula yeast (ETY; Arbiom, Raleigh, NC) are not different from values obtained in Menhaden fish meal (FM) was tested. In Exp. 1, 6 ileal cannulated barrows (11.7 ± 0.4 kg) were allotted to a replicated 3 × 3 Latin square with 3 diets (ETY, FM, and N-free) and 3 7-d periods. Ileal digesta were collected on d 6 and 7 of each period. Data were analyzed using the Proc Mixed with diet as main effect and pig as random effect. The SID of AA was greater (P < 0.05) in ETY than in FM (Table 1). In Exp. 2, 24 barrows (14.4 ± 1.1 kg) were individually housed in metabolism crates and allotted to a corn diet or diets based on corn and ETY or corn and FM. Feces and urine were collected for 5 d. Data were analyzed as in Exp. 1. No difference in ME between ETY (3,636 kcal/kg DM) and FM (3,611 kcal/kg DM) was observed. In Exp. 3, 32 barrows (11.9 ± 1.1 kg) were allotted to 4 diets in a 2 × 2 factorial with 2 ingredients (ETY and FM) and 0 or 500 units/kg of phytase. Housing and fecal sample collection was as in Exp. 2. Data were analyzed as in Exp. 1 with diet and phytase as main effects. Phytase did not influence STTD of P, but the STTD of P in the ETY (91%) was greater (P < 0.05) than in FM (68%). In conclusion, the SID of AA and the STTD of P in ETY is greater than in FM, but the ME in ETY is not different from FM.
Solving the SLAM (Simultaneous Localization And Mapping) problem increases the robot autonomy allowing the robot to build a map of the environment and simultaneously, estimate its pose (position and orientation) using this map. Usually, the robot pose is computed by means of odometry. This method uses the sensor information, nevertheless, these sensors introduce noise on the measurements, generating uncertainty in robot localization. For this reason, probabilistic methods as Kalman and Particle filters have been implemented in robotics to estimate the robot and landmark positions, manipulating the system errors.In this paper SLAM algorithms based Rao-Blackwellized particle filters were implemented in a mobile robotic platform to perform two-dimensional and three-dimensional unknown environments reconstructions. The SURF (Speed Up Robust Features) and RANSAC (Random Sample Consensus) methods were implemented for the visual feature extractions and the transformation estimations respectively. Furthermore, ROS (Robot Operating System) was used for platform position estimation and map building. Finally, a Monte Carlo algorithm was employed for autonomous navigation. This algorithm computes the shortest path between two points within the reconstructed map and executes it avoiding obstacles that may arise in its travel.
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