Objective To develop a causal model for the occurrence of neurocysticercosis (NC)‐related seizures and test hypotheses generated from the model. Methods We used data from a randomized controlled trial comparing albendazole with placebo among patients newly diagnosed with NC. Based on our causal model, we explored the associations among albendazole treatment, NC cyst evolution, and seizure outcomes over 24 months of follow‐up using generalized linear mixed effect models. Results We included 153 participants, of whom 51% received albendazole. The association between seizure outcomes and treatment over time demonstrated lack of linearity and heterogeneity, requiring the inclusion of time‐treatment interaction terms for valid modeling. Participants in the albendazole group had fewer seizures overall and of partial onset at all time points compared with the placebo group, but the difference increased over the first few months following treatment, then decreased over time. Generalized seizures exhibited a more complex association; those in the albendazole group had fewer seizures compared with those in the placebo group for the first few months after treatment, and then the association reversed and those in the placebo arm had fewer seizures. Adjusting for the number of NC cysts in each phase resulted in an attenuation of the strength of association between albendazole and seizure outcomes, consistent with mediation. Among participants in whom all cysts had disappeared (n = 21), none continued to have seizures. Significance Albendazole treatment is associated with a possible reduction in focal seizures in the short term (3‐6 months), perhaps by hastening the resolution of the cysts. However, the effect is not discernible over the long term, because most cysts either calcify or resolve completely, regardless of whether treated with albendazole. The stage of evolution of the cysticercus is an important consideration in the evaluation of albendazole effect on seizure outcome.
In this proposal, a real time bias estimation system for an airport surveillance data fusion system is presented. This bias estimation system is divided in two main parts. The first part estimates SMR bias terms, taking advantage of the knowledge of the airport map, which is useful because aircraft usually follow the axis of airport taxiways. The other part makes use of SMR corrected measures, which can be assumed to be unbiased. Using them, bias estimators for other important surface surveillance sensors are defined. These estimators are based on processing differences of measurement taken from each sensor and from the SMR. As simulation results show, if the sensor error models are precise enough, both estimations converge to the real bias values, and therefore unbiased measures may be obtained. These unbiased measurements should be provided to the fusion system, in order to enhance tracking performance. These estimation processes do not represent an important computer load increase for the data fusion system. The performance improvement in tracking is also presented.
La inteligencia artificial (IA) ha comenzado a ser parte de los procesos y de las rutinas periodísticas en muchos medios de comunicación. A nivel mundial existen algunos ejemplos, tanto en el periodismo escrito como en el audiovisual, que nos dan a entender que muy pronto la IA estará acompañándonos dentro de nuestros trabajos. El estudio que a continuación se presenta forma parte de los trabajos del grupo de investigación Comunicación y Cultura Audiovisual, de la Universidad Técnica Particular de Loja. El proyecto que diseñamos se llama «Historias de a Lata». Se trata de varios pódcast de corta duración donde, además de las narraciones, están de por medio actores naturales y artificiales. La investigación tenía como objetivo determinar, en base a la serie «Historias de a Lata», la influencia que la inteligencia artificial, concretamente la robótica TTS, podía ejercer dentro de la narración sonora. El método utilizado para obtener los datos sobre la valoración de la propuesta partía de técnicas cualitativas y cuantitativas. Por un lado, se aplicó una encuesta a estudiantes de comunicación que cursaban la materia de Radio y Nuevas Tecnologías sobre la base de dos preguntas principales: «¿Cuál es la sensación que le produce escuchar esta narración que incluye voces robóticas?» y «¿En qué géneros radiofónicos ven pertinente su aplicación?». Por otro lado, la investigación fue complementada con entrevistas a expertos internacionales del campo de la producción sonora. Como conclusión podemos afirmar que las personas sienten agrado por este tipo de producciones, aunque saben que de por medio hay voces artificiales. Además, manifestaron sentir indiferencia por las voces, incluso les distrae y les llama la atención. Algunos de los expertos complementaron los resultados señalando que la IA cada vez va creciendo más, desarrollando algoritmos que permiten hacer actividades impensadas. Ven su uso como parte del futuro de la producción sonora.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.