Using Machine Learning Algorithms on Electroencephalographic Signals to Assess Engineering Students' Focus While Solving Math Exercises / Uso de Algoritmos de Aprendizaje Automático en Señales Electroencefalográficas para Evaluar la Concentración de Estudiantes de Ingeniería al Resolver Ejercicios Matemáticos

Abstract In this paper, we present an attention classification method using Machine-Learning Algorithms. The EEG signals were recorded from ten engineering students with an EPOC+BCI using the electrodes F3, F4, P7, and P8 while solving some mathematical operations. The recording time for these activities is around 20 minutes. Next, a similar time EEG register is obtained while doing non-academic activities, such as chattering with the staff, checking cell phones, or playing a video game. With these EEG registers, we obtained a set of features to train and evaluate attention using Machine Learning algorithms. This research shows how engineering students interact with math topics in solving mental operations and complex reasoning by increasing brain domain and knowledge for mathematical reasoningrelated processes, such as sustained and shifting attention and logical constructions for object interaction during operations resolution. The Random Forest algorithm (RF) obtained the highest accuracy with 0.7392, an F1 Score of 0.7430, and the highest Specificity/Accuracy with 0.7261.

Resumen Se presenta un método de clasificación de la atención utilizando algoritmos de aprendizaje automático. Con las señales EEG de diez estudiantes de ingeniería adquiridas utilizando los electrodos F3, F4, P7 y P8 de una BCI EPOC+ mientras resuelven productos escalares, multiplicaciones algebraicas simples, simplificaciones e integrales por aproximadamente 20 minutos. Posteriormente, se obtiene un registro EEG de tiempo similar mientras se realizan actividades no académicas, como charlar con el personal, consultar el móvil o jugar a un videojuego. Se obtienen algunas características/parámetros, se entrenan y evalúan varios algoritmos de aprendizaje automático para la clasificación de la atención. Los resultados de esta investigación pueden mejorar la forma en que los estudiantes de ingeniería interactúan con los temas matemáticos en la resolución de operaciones mentales y razonamientos complejos, aumentando el dominio y el conocimiento cerebral para los procesos relacionados con el razonamiento matemático, como la atención sostenida y cambiante y las construcciones lógicas para la interacción con objetos durante la resolución de operaciones. El clasificador Random Forest obtuvo la mayor precisión con 0.7392, una puntuación F1 de 0.7430 y la mayor especificidad/precisión con 0.7261.

Antiviral activity in vitro and in vivo of natural flavonoids isolated from Heliotropium sinuatum against infectious salmon anemia virus (ISAV) / Actividad antiviral in vitro e in vivo de flavonoides naturales aislados desde Heliotropium sinuatum contra el virus de la anemia infecciosa en salmones (ISAV)

The infectious salmon anemia virus (ISAV) of Orthomyxoviridae family, is responsible for heavy losses in industry aquaculture around the world, affecting several commercial aquatic organisms, mainly Salmo salar. Therefore, it is important to find effective antiviral therapies. In this work we evaluated in vitro and in vivo the antiviral activity of three natural flavonoids isolated from the resinous exudates of the plant Heliotropium sinuatum (Heliotropiaceae) against ISAV. The results show that 7-O-methyleriodictyol was able to inhibit the infectivity of ISAV in vitro assay with EC 50 of 0.20 ug/mL. Despite having a citotoxicity expressed as CC50 of 12.80 ug/mL, the in vivo study showed that this compound protected 100 percent to the fish infected with ISAV keeping 100 percent fish viability. These results allow the proposal of 7-O-methyleriodictyol as a good candidate to be used as antiviral therapy for ISAV in salmon industry.

El virus de la anemia infecciosa en salmón de la familia Orthomyxoviridae, es el responsable de grandes pérdidas en la industria acuícola alrededor del mundo, afectando diversas especies acuáticas comerciales, principalmente Salmo salar. Por lo tanto, es muy importante encontrar una terapia antiviral efectiva. En el presente trabajo, evaluamos la actividad antiviral in vitro e in vivo de tres flavonoides naturales aislados desde el exudado resinoso de la especie vegetal Heliotropium sinuatum (Heliotropiaceae) contra ISAV. Los resultados mostraron que 7-O-metileriodictiol inhibió la infectividad de ISAV in vitro con un EC50 de 0.20 ug/mL. A pesar de tener una citotoxicidad expresada como un CC50 de 12.80 ug/mL, el estudio in vivo mostró que este compuesto protege en un 100 por ciento a los peces infectados con ISAV manteniendo un 100 por ciento de viabilidad. Estos resultados permiten proponer que 7-O-metileriodictiol es un buen candidato para ser usado como terapia antiviral para ISAV en la industria salmonera.

Protein synthesis in eukaryotes: The growing biological relevance of cap-independent translation initiation

Ribosome recruitment to eukaryotic mRNAs is generally thought to occur by a scanning mechanism, whereby the 40S ribosomal subunit binds in the vicinity of the 5'cap structure of the mRNA and scans until an AUG codon is encountered in an appropriate sequence context. Study of the picornaviruses allowed the characterization of an alternative mechanism of translation initiation. Picornaviruses can initiate translation via an internal ribosome entry segment (IRES), an RNA structure that directly recruits the 40S ribosomal subunits in a cap and 5' end independent fashion. Since its discovery, the notion of IRESs has extended to a number of different virus families and cellular RNAs. This review summarizes features of both cap-dependent and IRES-dependent mechanisms of translation initiation and discusses the role of cis-acting elements, which include the 5'cap, the 5'-untranslated region (UTR) and the poly(A) tail as well as the possible roles of IRESs as part of a cellular stress response mechanism and in the virus replication cycle.