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The advancement of genetic sequencing techniques led to the production of a large volume of data. The extraction of genetic material from a sample is one of the early steps of the metagenomic study. With the evolution of the processes, the analysis of the sequenced data allowed the discovery of etiological agents and, by corollary, the diagnosis of infections. One of the biggest challenges of the technique is the huge volume of data generated with each new technology developed. To introduce an algorithm that may reduce the data volume, allowing faster DNA matching with the reference databases. Using techniques like lossy compression and substitution matrix, it is possible to match nucleotide sequences without losing the subject. This lossy compression explores the nature of DNA mutations, insertions and deletions and the possibility that different sequences are the same subject. The algorithm can reduce the overall size of the database to 15% of the original size. Depending on parameters, it may reduce up to 5% of the original size. Although is the same as the other platforms, the match algorithm is more sensible because it ignores the transitions and transversions, resulting in a faster way to obtain the diagnostic results. The first experiment results in an increase in speed 10 times faster than Blast while maintaining high sensitivity. This performance gain can be extended by combining other techniques already used in other studies, such as hash tables. Database URL https://github.com/ghc4/metagens.

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Computerized simulators are important tools that support teaching in many areas. The use of these instruments is often described as significant for students and teachers. In this paper, a software piece was developed to aid decision-making in nursing, allowing the simulation of real situations, addressed in the classroom. The simulator architecture corresponds to a multi-agent system supported by a state machine model. To build the knowledge base, a list of contents was selected, including the Nursing Intervention Classification (NIC). An experiment was carried out with the participation of eleven students of the third year of the course. A questionnaire was applied and, as a result, there were more than 90% of acceptance as a relevant educational tool. The simulation, through this tool, contributed to apply theoretical knowledge to the students, besides helping in the development of the nursing decision-making ability.

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OBJECTIVE: To measure nursing Workload (WL) of nurses who work in the Inpatient Unit, as recommended by the Nursing Interventions Classification (NIC), comparing observational and online methods to propose supervision strategies for academic professionals. METHOD: Quantitative, descriptive, observational study performed in a Clinical/Surgical Hospital Unit. 30 direct and indirect activities. Data collected in observational and online records. Statistical analysis: SPSS 18.0 software, percentage frequencies and associated times between groups by Fisher's Exact test, 95% confidence interval, significance level 5%. RESULTS: Comparing the activities performed with the NIC time: from the direct 16, five observational and five online, were out of range, with no significant difference between frequencies (P=0.427). Of the 14 indirect, only in the observational, two were out of the range, without significant difference (P=0.486). CONCLUSION: Both methods measure WL; the online method developed accompanies activities performed in real time.

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ABSTRACT Objective: To measure nursing Workload (WL) of nurses who work in the Inpatient Unit, as recommended by the Nursing Interventions Classification (NIC), comparing observational and online methods to propose supervision strategies for academic professionals. Method: Quantitative, descriptive, observational study performed in a Clinical/Surgical Hospital Unit. 30 direct and indirect activities. Data collected in observational and online records. Statistical analysis: SPSS 18.0 software, percentage frequencies and associated times between groups by Fisher's Exact test, 95% confidence interval, significance level 5%. Results: Comparing the activities performed with the NIC time: from the direct 16, five observational and five online, were out of range, with no significant difference between frequencies (P=0.427). Of the 14 indirect, only in the observational, two were out of the range, without significant difference (P=0.486). Conclusion: Both methods measure WL; the online method developed accompanies activities performed in real time.

RESUMEN Objetivo: Medir la carga de trabajo (CT) de los enfermeros que actúan en Unidad de Internación, según preconiza la Nursing Interventions Classification (NIC), comparando los métodos observacional y online, para proponer estrategias de supervisión de los profesionales y académicos. Método: Estudio observacional descriptivo cuantitativo realizado en una Unidad de Internación Clínica/Quirúrgica. 30 actividades directas e indirectas. Datos recogidos en registros observacionales y en línea. Análisis estadístico: Software SPSS 18.0, frecuencias porcentuales y tiempos asociados entre grupos por la prueba Exacto de Fisher, intervalo de confianza 95%, nivel de significancia 5%. Resultados: Comparando las actividades realizadas con el tiempo preconizado por la NIC: de las 16 directas, cinco en el observacional y cinco en el on-line, estaban fuera del intervalo, sin diferencia significativa entre frecuencias (P=0,427). De las 14 indirectas, sólo en el observacional, dos estaban fuera del intervalo, sin diferencia significativa (P=0,486). Conclusión: Ambos métodos sirven para medir CT; el método online desarrollado acompaña actividades ejecutadas en tiempo real.

RESUMO Objetivo: Mensurar a Carga de Trabalho (CT) dos enfermeiros que atuam em Unidade de Internação, conforme preconiza a Nursing Interventions Classification (NIC), comparando os métodos observacional e on-line, para propor estratégias de supervisão dos profissionais eacadêmicos. Método: Estudo observacional descritivo quantitativo realizado em uma Unidade de Internação Clínica/Cirúrgica. 30 atividades diretas e indiretas. Dados levantados em registros observacional e on-line. Análise estatística: Software SPSS 18.0, frequências percentuais e tempos associadas entre grupos pelo teste Exato de Fisher, intervalo de confiança 95%, nível de significância 5%. Resultados: Comparando as atividades executadas com o tempo preconizado pela NIC: das 16 diretas, cinco no observacional e cinco no on-line, estavam fora do intervalo, sem diferença significativa entre frequências (P=0,427). Das 14 indiretas, apenas no observacional, duas estavam fora do intervalo, sem diferença significativa (P=0,486). Conclusão: Ambos os métodos servem para medir CT; o método on-line desenvolvido acompanha atividades executadas em tempo real.

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This work aims to describe the inception and design for a hospital simulator based on data and cases provided by teachers and other randomized data. The main goal is to develop a computer software tool that simulates a hospital as a tool for nursing student. The system is based on a multi-agent model and multi threaded parallel processing. Other parts includes the interfaces for teacher and student, reports and fixed constraints like Laws and other rules. This is a work in progress project and will be released as open source software after the final validation.

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