The aporophobia in the context of Peruvian society: a review

Rosmery Sabina Pozo Enciso Óscar Arbieto Mamani (2021)

The research begins by theorizing about aporophobia, a concept approved by the Royal Spanish Academy to refer a phobia over the poor. Documents and reports from national and international organizations were reviewed to characterize, analyze and conceptualize aporophobia, defining the relationship between poverty and discrimination in Peru. A descriptive statistical analysis was conducted to visualize tendencies in discrimination and poverty indicators. In addition, correlation analysis was applied using the Pearson R coefficient with a 0.05 significance. There was a very strong and positive correlation between discrimination and poverty, however the complexity of the concept led to the conclusion where there is a trend towards ethnic cultural discrimination and racial self-discrimination.

Article

Artículo

Aporofobia Pobreza Discriminación Naturaleza humana Identidad étnica CIENCIAS SOCIALES CIENCIAS SOCIALES Aporophobia poverty discrimination human nature ethnic identity

Triborheological analysis of reconstituted gastrointestinal porcine mucus / chitosan:TPP nanoparticles system for studying mucoadhesion under different pH conditions

GUSTAVO RUIZ PULIDO (2022)

https://orcid.org/0000-0001-5325-0079

The use of biodegradable polymers as vehicles for administration and long-term release of drugs has great relevance in the delivery of new generation therapeutic agents, such as: amino acids, peptides, proteins, antibodies, nucleic acids, among others. Because biomolecules are metabolized or excreted after short periods within the body, which are usually shorter than time required to observe their therapeutic effect or to reach the site of action. For that reason, the encapsulation of biomolecules in microspheres or nanoparticles represents a method of interest for biopharmaceuticals administration.

Additionally, the phenomenon of mucoadhesion has been studied as an alternative to increase the residence time of nanocarriers within the body and, consequently, increase the half-life and cell permeability of biomolecules, allowing them to reach the level of bioavailability necessary to carry out its therapeutic activity when administered orally.

Chitosan nanoparticles were analyzed as a possible mucoadhesive vehicle for drug delivery based on their cationic nature that exhibits a high degree of interaction with negatively charged mucus functional groups. However, chitosan presents significant changes in its surface charge throughout the gastrointestinal tract due to variations in pH, affecting its mucoadhesive properties.

This project proposed the analysis of the interaction between reconstituted gastrointestinal porcine mucus and chitosan:TPP nanoparticles under gastrointestinal pH conditions (pH = 2.0 – 7.0) from a triborheological point of view. Considering that rheological synergism represents an indirect method to evaluate the presence or absence of mucoadhesion phenomenon based on the strength of the interfacial layer between mucus and nanoparticles, which is measured by the increase of viscosity (η) or elastic modulus (G’) in the mixture of mucus-nanoparticles as a result of the interpenetration of polymeric and mucin chains through electrostatic interactions and physical entanglement, mainly.

Therefore, triborheological tests were performed to characterize the viscoelastic, viscous, and lubricating profiles of reconstituted mucus at different pH conditions to examine the variations experienced by the mucus along the gastrointestinal tract. Similarly, triborheological synergism analyzes were performed to determine under which pH values the mucoadhesion phenomenon occurs, revealing that chitosan:TPP exhibit mucoadhesiveness at conditions below its value of pKa (6.5). Whereas, under neutral environment or above to their pKa value, chitosan:TPP nanoparticles do not exhibit the mucoadhesion properties.

Doctor of Philosophy In Nanotechnology

Article

MEDICINA Y CIENCIAS DE LA SALUD CIENCIAS MÉDICAS BIOLOGÍA HUMANA FARMACOLOGÍA MOLECULAR

Reconocimiento de emociones a partir de patrones en la marcha humana

Recognition of emotions from patterns in the human gait

Yulith Vanessa Altamirano Flores (2023)

El análisis de la marcha humana se ha utilizado ampliamente en el campo clínico, por ejemplo, para el diagnóstico temprano de algunas enfermedades. Por otro lado, es posible asociar patrones de movimiento durante la marcha con varios comportamientos humanos, como las emociones. El objetivo principal de esta tesis es generar modelos para clasificar tres emociones discretas: feliz, triste y enojado, considerando el estado neutral como una clase adicional, utilizando un conjunto de características extraídas de la posición 3D del esqueleto humano durante sesiones de marcha. Se realizó un análisis descriptivo de los datos para seleccionar los mejores subconjuntos de articulaciones para reconocer estas emociones. Los modelos se construyeron con los algoritmos: KNN, Random Forest y un meta-clasificador (Boosting). Los mejores resultados se obtuvieron con Boosting con el método de selección PCA con un mAP de 0.840 para datos balanceados y Random Forest con el método de selección UVA con un mAP de 0.886 para datos desbalanceados. Los resultados fueron prometedores al utilizar métodos basados en aprendizaje automático superficial.

Human gait analysis has been widely used in the clinical field, for example, for the early diagnosis of some diseases. On the other hand, it is possible to associate movement patterns during gait with various human behaviors, such as emotions. The main objective of this thesis is to generate models to classify three discrete emotions: happy, sad and angry, considering the neutral state as an additional class, using a set of features extracted from the 3D position of the human skeleton during walking sessions. A descriptive analysis of the data was performed to select the best subsets of joints to recognize these emotions. The models were built with the algorithms: KNN, Random Forest and a meta-classifier (Boosting). The best results were obtained with Boosting with the PCA selection method with a mAP of 0.840 for balanced data and Random Forest with the UVA selection method with a mAP of 0.886 for unbalanced data. The results were promising when using methods based on shallow machine learning.

Master thesis

Reconocimiento de emociones, emociones, clasificación de emociones, marcha humana, aprendizaje Emotions, emotion recognition, emotion classification, human gait, machine learning INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES DISEÑO CON AYUDA DE ORDENADOR DISEÑO CON AYUDA DE ORDENADOR