Percepció de l’impacte del moviment Occupy Wall Street tres anys després de les acampades

Treballs Finals de Grau en Estadística UB-UPC, Facultat d'Economia i Empresa (UB) i Facultat de Matemàtiques i Estadística (UPC), Curs: 2014-2015, Tutor: Mireia Fernández-ArdèEl moviment Occupy Wall Street va sorgir el 2011 als Estats Units d’Amèrica com una crítica d’alguns sectors degut a situacions d’injustícia percebudes. Un moviment que va anar estenent-se arreu del territori i va causar moltes opinions i emocions diferents entre els seus participants i la resta de col·lectius. Per això, el present treball intentarà donar resposta a algunes preguntes sobre l’heterogeneïtat i la transformació d’emocions, estudiant des d’un punt de vista estadístic l’evolució de les emocions percebudes durant el moment de les acampades i tres anys després. El mitjà utilitzat per a fer-ho ha sigut amb dades secundàries obtingudes a través d’una enquesta per Internet realitzada a finals de 2014 amb més de 500 observacions

Trust, Accountability, and Autonomy in Knowledge Graph-based AI for Self-determination

Knowledge Graphs (KGs) have emerged as fundamental platforms for powering intelligent decision-making and a wide range of Artificial Intelligence (AI) services across major corporations such as Google, Walmart, and AirBnb. KGs complement Machine Learning (ML) algorithms by providing data context and semantics, thereby enabling further inference and question-answering capabilities. The integration of KGs with neuronal learning (e.g., Large Language Models (LLMs)) is currently a topic of active research, commonly named neuro-symbolic AI. Despite the numerous benefits that can be accomplished with KG-based AI, its growing ubiquity within online services may result in the loss of self-determination for citizens as a fundamental societal issue. The more we rely on these technologies, which are often centralised, the less citizens will be able to determine their own destinies. To counter this threat, AI regulation, such as the European Union (EU) AI Act, is being proposed in certain regions. The regulation sets what technologists need to do, leading to questions concerning: How can the output of AI systems be trusted? What is needed to ensure that the data fuelling and the inner workings of these artefacts are transparent? How can AI be made accountable for its decision-making? This paper conceptualises the foundational topics and research pillars to support KG-based AI for self-determination. Drawing upon this conceptual framework, challenges and opportunities for citizen self-determination are illustrated and analysed in a real-world scenario. As a result, we propose a research agenda aimed at accomplishing the recommended objectives

Trust, Accountability, and Autonomy in Knowledge Graph-Based AI for Self-Determination

Knowledge Graphs (KGs) have emerged as fundamental platforms for powering intelligent decision-making and a wide range of Artificial Intelligence (AI) services across major corporations such as Google, Walmart, and AirBnb. KGs complement Machine Learning (ML) algorithms by providing data context and semantics, thereby enabling further inference and question-answering capabilities. The integration of KGs with neuronal learning (e.g., Large Language Models (LLMs)) is currently a topic of active research, commonly named neuro-symbolic AI. Despite the numerous benefits that can be accomplished with KG-based AI, its growing ubiquity within online services may result in the loss of self-determination for citizens as a fundamental societal issue. The more we rely on these technologies, which are often centralised, the less citizens will be able to determine their own destinies. To counter this threat, AI regulation, such as the European Union (EU) AI Act, is being proposed in certain regions. The regulation sets what technologists need to do, leading to questions concerning How the output of AI systems can be trusted? What is needed to ensure that the data fuelling and the inner workings of these artefacts are transparent? How can AI be made accountable for its decision-making? This paper conceptualises the foundational topics and research pillars to support KG-based AI for self-determination. Drawing upon this conceptual framework, challenges and opportunities for citizen self-determination are illustrated and analysed in a real-world scenario. As a result, we propose a research agenda aimed at accomplishing the recommended objectives

Development of a novel anti-CD19 chimeric antigen receptor: A paradigm for an affordable CAR T cell production at academic institutions

Genetically modifying autologous T cells to express an anti-CD19 chimeric antigen receptor (CAR) has shown impressive response rates for the treatment of CD19+ B cell malignancies in several clinical trials (CTs). Making this treatment available to our patients prompted us to develop a novel CART19 based on our own anti-CD19 antibody (A3B1), followed by CD8 hinge and transmembrane region, 4-1BB- and CD3z-signaling domains. We show that A3B1 CAR T cells are highly cytotoxic and specific against CD19+ cells in vitro, inducing secretion of pro-inflammatory cytokines and CAR T cell proliferation. In vivo, A3B1 CAR T cells are able to fully control disease progression in an NOD.Cg-Prkdcscid Il2rdtm1Wjl/SzJ (NSG) xenograph B-ALL mouse model. Based on the pre-clinical data, we conclude that our CART19 is clearly functional against CD19+ cells, to a level similar to other CAR19s currently being used in the clinic. Concurrently, we describe the implementation of our CAR T cell production system, using lentiviral vector and CliniMACS Prodigy, within a medium-sized academic institution. The results of the validation phase show our system is robust and reproducible, while maintaining a low cost that is affordable for academic institutions. Our model can serve as a paradigm for similar institutions, and it may help to make CAR T cell treatment available to all patients

Textos sobre educación universitaria: la docencia de la estadística (2017)

Esta publicación recopila las distintas contribuciones del Grupo de Innovación Docente Consolidado “ANDES - Análisis de Datos en Economía y Empresa” sobre la innovación docente en el amplio universo del análisis de datos. Esta obra tiene como objetivo hacer llegar a los docentes universitarios y a los interesados en la docencia universitaria la investigación y la innovación que se producen en este ámbito. El Grupo de Innovación Docente Consolidado “ANDES” tiene como objetivos estudiar, analizar, ajustar y movilizar los recursos y acciones necesarias para mejorar la docencia de la Estadística y otras asignaturas de análisis de datos, que se dirigen a estudiantes de diferentes Grados, como Estadística, ADE, Economía, etc. Fundamentalmente, el trabajo de innovación docente se focaliza en asignaturas obligatorias y troncales de los Grados mencionados.Este texto ha sido llevado a cabo en el marco del proyecto 2013PID-UB/004. Agradecemos a la Universitat de Barcelona su apoyo y financiación.Projecte 2013PID-UB/00

Pasados y presente. Estudios para el profesor Ricardo García Cárcel

Ricardo García Cárcel (Requena, 1948) estudió Historia en Valencia bajo el magisterio de Joan Reglà, con quien formó parte del primer profesorado de historia moderna en la Universidad Autónoma de Barcelona. En esta universidad, desde hace prácticamente cincuenta años, ha desarrollado una extraordinaria labor docente y de investigación marcada por un sagaz instinto histórico, que le ha convertido en pionero de casi todo lo que ha estudiado: las Germanías, la historia de la Cataluña moderna, la Inquisición, las culturas del Siglo de Oro, la Leyenda Negra, Felipe II, Felipe V, Austrias y Borbones, la guerra de la Independencia, la historia cultural, los mitos de la historia de España... Muy pocos tienen su capacidad para reflexionar, ordenar, analizar, conceptualizar y proponer una visión amplia y llena de matices sobre el pasado y las interpretaciones historiográficas. A su laboriosidad inimitable se añade una dedicación sin límites en el asesoramiento de alumnos e investigadores e impulsando revistas, dosieres, seminarios o publicaciones colectivas. Una mínima correspondencia a su generosidad lo constituye este volumen a manera de ineludible agradecimiento

All-cause mortality in the cohorts of the Spanish AIDS Research Network (RIS) compared with the general population: 1997Ł2010

Abstract Background: Combination antiretroviral therapy (cART) has produced significant changes in mortality of HIVinfected persons. Our objective was to estimate mortality rates, standardized mortality ratios and excess mortality rates of cohorts of the AIDS Research Network (RIS) (CoRIS-MD and CoRIS) compared to the general population. Methods: We analysed data of CoRIS-MD and CoRIS cohorts from 1997 to 2010. We calculated: (i) all-cause mortality rates, (ii) standardized mortality ratio (SMR) and (iii) excess mortality rates for both cohort for 100 personyears (py) of follow-up, comparing all-cause mortality with that of the general population of similar age and gender. Results: Between 1997 and 2010, 8,214 HIV positive subjects were included, 2,453 (29.9%) in CoRIS-MD and 5,761 (70.1%) in CoRIS and 294 deaths were registered. All-cause mortality rate was 1.02 (95% CI 0.91-1.15) per 100 py, SMR was 6.8 (95% CI 5.9-7.9) and excess mortality rate was 0.8 (95% CI 0.7-0.9) per 100 py. Mortality was higher in patients with AIDS, hepatitis C virus (HCV) co-infection, and those from CoRIS-MD cohort (1997. Conclusion: Mortality among HIV-positive persons remains higher than that of the general population of similar age and sex, with significant differences depending on the history of AIDS or HCV coinfection

Percepció de l’impacte del moviment Occupy Wall Street tres anys després de les acampades

El moviment Occupy Wall Street va sorgir el 2011 als Estats Units d’Amèrica com una crítica d’alguns sectors degut a situacions d’injustícia percebudes. Un moviment que va anar estenent-se arreu del territori i va causar moltes opinions i emocions diferents entre els seus participants i la resta de col·lectius. Per això, el present treball intentarà donar resposta a algunes preguntes sobre l’heterogeneïtat i la transformació d’emocions, estudiant des d’un punt de vista estadístic l’evolució de les emocions percebudes durant el moment de les acampades i tres anys després. El mitjà utilitzat per a fer-ho ha sigut amb dades secundàries obtingudes a través d’una enquesta per Internet realitzada a finals de 2014 amb més de 500 observacions

Trust, accountability, and autonomy in knowledge graph-based AI for self-determination

Knowledge Graphs (KGs) have emerged as fundamental platforms for powering intelligent decision-making and a wide range of Artificial Intelligence (AI) services across major corporations such as Google, Walmart, and AirBnb. KGs complement Machine Learning (ML) algorithms by providing data context and semantics, thereby enabling further inference and question-answering capabilities. The integration of KGs with neuronal learning (e.g., Large Language Models (LLMs)) is currently a topic of active research, commonly named neuro-symbolic AI. Despite the numerous benefits that can be accomplished with KG-based AI, its growing ubiquity within online services may result in the loss of self-determination for citizens as a fundamental societal issue. The more we rely on these technologies, which are often centralised, the less citizens will be able to determine their own destinies. To counter this threat, AI regulation, such as the European Union (EU) AI Act, is being proposed in certain regions. The regulation sets what technologists need to do, leading to questions concerning: How can the output of AI systems be trusted? What is needed to ensure that the data fuelling and the inner workings of these artefacts are transparent? How can AI be made accountable for its decision-making? This paper conceptualises the foundational topics and research pillars to support KG-based AI for self-determination. Drawing upon this conceptual framework, challenges and opportunities for citizen self-determination are illustrated and analysed in a real-world scenario. As a result, we propose a research agenda aimed at accomplishing the recommended objectives