Sara Correidora Darriba. Constelaciones en la Educación. Tomar y traspasar "las monedas".

Sara Correidora Darriba. Constelaciones en la Educación. Tomar y traspasar "las monedas".

Marian Roig Estellés: Investigación y Constelaciones Familiares. El origen transgeneracional de los Sueños

Marian Roig Estellés: Investigación y Constelaciones Familiares. El origen transgeneracional de los Sueños

Rosa Valera Garay. Intervención Sistemática con adolescentes en la violencia escolar

Rosa Valera Garay. Intervención Sistemática con adolescentes en la violencia escolar

Sara Rodríguez Simón: Investigación y Constelaciones Familiares. El salto cuántico en las relaciones de pareja en el s.XXI

Sara Rodríguez Simón: Investigación y Constelaciones Familiares. El salto cuántico en las relaciones de pareja en el s.XXI

Bertold Usamer.Apertura del Congreso.Constelaciones y Diversidad

Bertold Usamer.Apertura del Congreso.Constelaciones y Diversidad

Manuel Zapata García. Apertura del Congreso. Configuraciones arquetípicos: Su uso en la terapia y constelaciones

Manuel Zapata García. Apertura del Congreso. Configuraciones arquetípicos: Su uso en la terapia y constelaciones

Maria del Mar Rodríguez Simón. La diversidad en la Armonía. Apertura del Congreso

Maria del Mar Rodríguez Simón. La diversidad en la Armonía. Apertura del Congreso

La ciudad en la narrativa latinoamericana: 1950-1975

The representation of the city has always been present in the literature. A clear example of this is the famous city of Troy. The city in terms of where the actions take place, a novel in this case, despite the efforts of some works of the contemporary narrative to eradicate or reduce to its barest minimum expression, has continued to sit as a strong element of differentiation that gives the characters certain linguistic, historical, social and cultural characteristics. In the Hispanic narrative, according to historical features of the continent, the conquest, independence, and subsequently the constitution of the republics, the representation of the city acquires some unique characteristics, whose dimensions and implications, toward the second half of the twentieth century, transcend the simple notion of 'place' in which occur the facts narrated to acquire a central notion in the works, changing from being a support to become the central structure of the novel, which is able to articulate different situations, confront characters and articulate historically to the entire countries. This paper will talk mainly about the representation of the city in the published narrative between 1950 and 1975. We will try to have a transverse reading over these works through the analysis of the representation of the city that in them we can find, and that basically divided into three broad categories, each with its own specific functions: * The royal city. Corresponds to the cities that we can actually find in the American territory, and whose spaces and descriptions, historical references and territorial, it is possible to identify the reality or in any encyclopedia: streets, historical events, places, characters, etc...

Revisión sistemática utilidad de asa y calcio con o sin vitamina d en la prevención de cáncer colorrectal y la recurrencia de pólipos adenomatosos en paciente con riesgo de padecer esta patología

Introducción: El cáncer colorrectal es una patología con alto impacto en la salud pública, debido a su prevalencia, incidencia, severidad, costo e impacto en la salud mental y física del individuo y la familia. Ensayos clínicos realizados en pacientes con antecedente de infarto al miocardio que consumían ácido acetil salicílico (asa), calcio con y sin vitamina D, mostraron asociación entre el consumo de estos medicamentos y disminución en la incidencia en cáncer colorrectal y pólipos adenomatosos. Objetivo: Evaluar la literatura sobre el uso de asa, calcio con y sin vitamina D con relación a su impacto en la prevención del cáncer colorrectal y pólipos adenomatosos. Métodos: Se realizó revisión sistemática buscando ensayos clínicos realizados en pacientes con factores de riesgo para cáncer colorrectal y pólipos adenomatosos que usaron asa, calcio con y sin vitamina D fueron incluidos. Resultados: se escogieron 105 para la revisión sistemática. Conclusiones: Es necesario desarrollar más estudios que lleven a evaluar el efecto protector de la aspirina, calcio y vitamina D. En los artículos revisados la aspirina a dosis de 81 a 325 mg día se correlaciona con reducción de riesgo de aparición de CRC aunque la dosis ideal, el tiempo de inicio y la duración de la ingesta continua no son claros. Hacen falta estudios que comparen poblaciones con ingesta de asa a diferentes dosis.

BM: El comercio electrónico como plataforma de comercio internacional para Colombia

Las relaciones Internacionales hoy, se abordan bajo la óptica de la interdependencia Compleja caracterizada por variados canales de acción, una agenda múltiple no jerarquizada y la relevancia del conocimiento y la información, lo que desarrollará agilidad en los procesos, la consolidación del mundo 7 x 241, y la desaparición de las fronteras geográficas. Surge así una nueva visión de la política mundial que privilegia la interacción entre los distintos segmentos de las sociedades nacionales en función de múltiples intereses específicos, dentro de un mundo totalmente transnacionalizado, en el cual debe predominar el concepto de bienestar y específicamente, trabajar enfocados en políticas en materia de productividad y de competitividad por medio del comercio electrónico, para elevar los índices de comercio exterior. En este sentido, la multipolaridad2 se presenta como una característica que representa al sistema mundial de hoy, cuando los centros de poder luchan por desarrollar una infraestructura que apoye la base económica, política y social para impulsar la modernización. Hoy es un hecho, aceptado como natural, el que aunque el Estado siga ejerciendo un papel importante en el orden político internacional, progresivamente el monopolio y la centralización del poder sea disgregado en beneficio de los actores transnacionales, dando lugar a lo que se denomina el Estado de Competencia.

Advancing digital healthcare research and machine learning-aided knowledge extraction amidst the COVID-19 pandemic

The rapid progression of biomedical research coupled with the explosion of scientific literature has generated an exigent need for efficient and reliable systems of knowledge extraction. This dissertation contends with this challenge through a concentrated investigation of digital health, Artificial Intelligence, and specifically Machine Learning and Natural Language Processing's (NLP) potential to expedite systematic literature reviews and refine the knowledge extraction process. The surge of COVID-19 complicated the efforts of scientists, policymakers, and medical professionals in identifying pertinent articles and assessing their scientific validity. This thesis presents a substantial solution in the form of the COKE Project, an initiative that interlaces machine reading with the rigorous protocols of Evidence-Based Medicine to streamline knowledge extraction. In the framework of the COKE (“COVID-19 Knowledge Extraction framework for next-generation discovery science”) Project, this thesis aims to underscore the capacity of machine reading to create knowledge graphs from scientific texts. The project is remarkable for its innovative use of NLP techniques such as a BERT + bi-LSTM language model. This combination is employed to detect and categorize elements within medical abstracts, thereby enhancing the systematic literature review process. The COKE project's outcomes show that NLP, when used in a judiciously structured manner, can significantly reduce the time and effort required to produce medical guidelines. These findings are particularly salient during times of medical emergency, like the COVID-19 pandemic, when quick and accurate research results are critical.

Quality and Aspect based Argument Generation

Natural Language Processing has always been one of the most popular topics in Artificial Intelligence. Argument-related research in NLP, such as argument detection, argument mining and argument generation, has been popular, especially in recent years. In our daily lives, we use arguments to express ourselves. The quality of arguments heavily impacts the effectiveness of our communications with others. In professional fields, such as legislation and academic areas, arguments of good quality play an even more critical role. Therefore, argument generation with good quality is a challenging research task that is also of great importance in NLP. The aim of this work is to investigate the automatic generation of arguments with good quality, according to the given topic, stance and aspect (control codes). To achieve this goal, a module based on BERT [17] which could judge an argument's quality is constructed. This module is used to assess the quality of the generated arguments. Another module based on GPT-2 [19] is implemented to generate arguments. Stances and aspects are also used as guidance when generating arguments. After combining all these models and techniques, the ranks of the generated arguments could be acquired to evaluate the final performance. This dissertation describes the architecture and experimental setup, analyzes the results of our experimentation, and discusses future directions.

Sviluppo di Retrieval-based Chatbot per l'Italiano con Transformer

L’Intelligenza Artificiale negli ultimi anni sta plasmando il futuro dell’umanità in quasi tutti i settori. È già il motore principale di diverse tecnologie emergenti come i big data, la robotica e l’IoT e continuerà ad agire come innovatore tecnologico nel futuro prossimo. Le recenti scoperte e migliorie sia nel campo dell’hardware che in quello matematico hanno migliorato l’efficienza e ridotto i tempi di esecuzione dei software. È in questo contesto che sta evolvendo anche il Natural Language Processing (NLP), un ramo dell’Intelligenza Artificiale che studia il modo in cui fornire ai computer l'abilità di comprendere un testo scritto o parlato allo stesso modo in cui lo farebbe un essere umano. Le ambiguità che distinguono la lingua naturale dalle altre rendono ardui gli studi in questo settore. Molti dei recenti sviluppi algoritmici su NLP si basano su tecnologie inventate decenni fa. La ricerca in questo settore è quindi in continua evoluzione. Questa tesi si pone l'obiettivo di sviluppare la logica di una chatbot help-desk per un'azienda privata. Lo scopo è, sottoposta una domanda da parte di un utente, restituire la risposta associata presente in una collezione domande-risposte. Il problema che questa tesi affronta è sviluppare un modello di NLP in grado di comprendere il significato semantico delle domande in input, poiché esse possono essere formulate in molteplici modi, preservando il contenuto semantico a discapito della sintassi. A causa delle ridotte dimensioni del dataset italiano proprietario su cui testare il modello chatbot, sono state eseguite molteplici sperimentazioni su un ulteriore dataset italiano con task affine. Attraverso diversi approcci di addestramento, tra cui apprendimento metrico, sono state raggiunte alte accuratezze sulle più comuni metriche di valutazione, confermando le capacità del modello proposto e sviluppato.

Hierarchical Multi-Label Text Classification in a Low-Resource Setting

In this thesis we address a multi-label hierarchical text classification problem in a low-resource setting and explore different approaches to identify the best one for our case. The goal is to train a model that classifies English school exercises according to a hierarchical taxonomy with few labeled data. The experiments made in this work employ different machine learning models and text representation techniques: CatBoost with tf-idf features, classifiers based on pre-trained models (mBERT, LASER), and SetFit, a framework for few-shot text classification. SetFit proved to be the most promising approach, achieving better performance when during training only a few labeled examples per class are available. However, this thesis does not consider all the hierarchical taxonomy, but only the first two levels: to address classification with the classes at the third level further experiments should be carried out, exploring methods for zero-shot text classification, data augmentation, and strategies to exploit the hierarchical structure of the taxonomy during training.

Antibody-Antigen Interface Characterization with Contextualized Pre-trained Embeddings

Artificial Intelligence (AI) has substantially influenced numerous disciplines in recent years. Biology, chemistry, and bioinformatics are among them, with significant advances in protein structure prediction, paratope prediction, protein-protein interactions (PPIs), and antibody-antigen interactions. Understanding PPIs is critical since they are responsible for practically everything living and have several uses in vaccines, cancer, immunology, and inflammatory illnesses. Machine Learning (ML) offers enormous potential for effectively simulating antibody-antigen interactions and improving in-silico optimization of therapeutic antibodies for desired features, including binding activity, stability, and low immunogenicity. This research looks at the use of AI algorithms to better understand antibody-antigen interactions, and it further expands and explains several difficulties encountered in the field. Furthermore, we contribute by presenting a method that outperforms existing state-of-the-art strategies in paratope prediction from sequence data.