Ibero-American Research on Local Development. An Analysis of Its Evolution and New Trends

Local development is a subject that arouses significant interest in the international scientific community in general, and in the Ibero-American one, in particular. The process of globalization has transformed the management of local development, altering the role that is played by local and regional entities, and it is the object of an important follow-up and analysis by academia. This research uses a bibliometric methodology and a fractional counting method, reviewing the 738 articles from the Scopus database in order to understand the state of Ibero-American research on local development, and analyze the scientific literature on the topic. The results show a significant increase in the number of publications in the 21st century, with Spain and Brazil leading the way. In addition, this research provides interesting results regarding the most influential authors on this topic, the most relevant journals, and the most important institutions and funding organizations. There are several areas of knowledge involved since local development is a transversal field, such as Social Science, environment, business, economics, and agriculture. A deep analysis of authors’ keywords identified new trends, linking local development with tourism, education, geotourism, climate change, local sustainable development, social innovation, and creativity, which provides academia with potential new lines of research

Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth Maps

Self-supervised monocular depth estimation has been a subject of intense study in recent years, because of its applications in robotics and autonomous driving. Much of the recent work focuses on improving depth estimation by increasing architecture complexity. This paper shows that state-of-the-art performance can also be achieved by improving the learning process rather than increasing model complexity. More specifically, we propose (i) disregarding small potentially dynamic objects when training, and (ii) employing an appearance-based approach to separately estimate object pose for truly dynamic objects. We demonstrate that these simplifications reduce GPU memory usage by 29% and result in qualitatively and quantitatively improved depth maps. The code is available at https://github.com/kieran514/Dyna-DM

SocNavGym: A Reinforcement Learning Gym for Social Navigation

It is essential for autonomous robots to be socially compliant while navigating in human-populated environments. Machine Learning and, especially, Deep Reinforcement Learning have recently gained considerable traction in the field of Social Navigation. This can be partially attributed to the resulting policies not being bound by human limitations in terms of code complexity or the number of variables that are handled. Unfortunately, the lack of safety guarantees and the large data requirements by DRL algorithms make learning in the real world unfeasible. To bridge this gap, simulation environments are frequently used. We propose SocNavGym, an advanced simulation environment for social navigation that can generate a wide variety of social navigation scenarios and facilitates the development of intelligent social agents. SocNavGym is light-weight, fast, easy-to-use, and can be effortlessly configured to generate different types of social navigation scenarios. It can also be configured to work with different hand-crafted and data-driven social reward signals and to yield a variety of evaluation metrics to benchmark agents' performance. Further, we also provide a case study where a Dueling-DQN agent is trained to learn social-navigation policies using SocNavGym. The results provides evidence that SocNavGym can be used to train an agent from scratch to navigate in simple as well as complex social scenarios. Our experiments also show that the agents trained using the data-driven reward function displays more advanced social compliance in comparison to the heuristic-based reward function.Comment: IEEE RO-MA

Zaragoza Life Project: Creation, Management and Promotion of Green Infrastructure of Zaragoza (Spain). LIFE12 ENV/ES/000567

The City Hall of Zaragoza turned out to be beneficiary in the year 2012 of a European LIFE project called Life Zaragoza Natural. The general objective of the project is to protect, enhance, value, know and bring the Green Infrastructure (GI) of Zaragoza to the attention of the public, which includes Natura 2000 spaces (Sites of Community Importance (SCIs) and Special Protection Areas (SPAs)) as well as the Green Belt and other natural spaces of municipal interest to be considered of great uniqueness on European scale due to both its contiguity and proximity to a large city and its extraordinary state of conservation. This main objective is considered as a continuation of biodiversity management and environmental improvement policies held by Zaragoza City Council. It is considered as an opportunity for employment (according to green economy guidelines and the current economic crisis). Zaragoza is one of the largest municipal districts of Spain (nearly 1.000 Km2) Its peculiar location characterized by the passage of three rivers in a semidesert area provides the existence of exceptional natural heritage, with the coexistence of multiple landscapes. The biodiversity of approximately 40% of the municipal area is important to be preserved and is therefore protected both on Europe level, Natura 2000, and on national level. In addition, Zaragoza has an extensive network of parks, gardens and green areas which has taken a quantum and qualitative leap in the last decade in their green areas from having 3.200.000m2 to having over 8.270.000m2. Meanwhile, the General Urban Management Plan of Zaragoza establishes a classification system based on soil classification techniques (urban land, building land and undeveloped land) and rating as well as the regulation of uses, conditions for the protection and management of undeveloped land, generic or special. This is the first of instruments for the protection of natural values of the municipality. 52.000 hectares are urban protected as special undeveloped land

The reform of the portuguese pension system: a micro-simulation approach

Doutoramento em Estudos do DesenvolvimentoThis thesis uses a Dynamic Microsimulation Model (DYNAPOR) to analyse the impact of a transition from a traditional Defined Benefit Pay-As-You-Go pension scheme to a Notional Defined Contribution system on both the financial and the social sustainability of the pension system in Portugal. The results show that while the NDC scenarios outperform the DB-PAYG system in terms of financial sustainability, it does so at cost of the social component. Additionally, the various features of the NDC pension system are proven to be essential in both curbing expenditure and improving adequacy and poverty alleviation.Esta tese utiliza um modelo de micro-simulação dinâmico (DYNAPOR) para analisar o impacto económico, financeiro e social da transição de um sistema de pensões pay-as-you-go de benefício definido para um sistema de contas nocionais em Portugal. Utiliza o modelo DYNAPOR para simular quatro cenários diferentes. Os resultados obtidos sugerem que uma transição para um sistema de contas nocionais semelhante ao que está em vigor na Suécia se traduz num melhoramento significativo da sustentabilidade financeira em relação ao previsto no sistema atual. Contudo, este melhoramento na sustentabilidade financeira acontece em detrimento da componente social do sistema de pensões. Mais, o impacto da componente redistributiva e de balanço automático do sistema NDC no alívio da pobreza e da despesa é comprovado pelos resultados.N/

LearnBlock: A Robot-Agnostic Educational Programming Tool

Education is evolving to prepare students for the current sociotechnical changes. An increasing effort to introduce programming and other STEM-related subjects into the core curriculum of primary and secondary education is taking place around the world. The use of robots stands out among STEM initiatives, since robots are proving to be an engaging tool for learning programming and other STEM-related contents. Block-based programming is the option chosen for most educational robotic platforms. However, many robotics kits include their own software tools, as well as their own set of programming blocks. LearnBlock, a new educational programming tool, is proposed here. Its major novelty is its loosely coupled software architecture which makes it, to the best of our knowledge, the first robot-agnostic educational tool. Robot-agnosticism is provided not only in block code, but also in generated code, unifying the translation from blocks to the final programming language. The set of blocks can be easily extended implementing additional Python functions, without modifying the core code of the tool. Moreover, LearnBlock provides an integrated educational programming environment that facilitates a progressive transition from a visual to a general-purpose programming language. To evaluate LearnBlock and demonstrate that it is platform-agnostic, several tests were conducted. Each of them consists of a program implementing a robot behaviour. The block code of each test can run on several educational robots without changes

SocNav1: A Dataset to Benchmark and Learn Social Navigation Conventions

Datasets are essential to the development and evaluation of machine learning and artificial intelligence algorithms. As new tasks are addressed, new datasets are required. Training algorithms for human-aware navigation is an example of this need. Different factors make designing and gathering data for human-aware navigation datasets challenging. Firstly, the problem itself is subjective, different dataset contributors will very frequently disagree to some extent on their labels. Secondly, the number of variables to consider is undetermined culture-dependent. This paper presents SocNav1, a dataset for social navigation conventions. SocNav1 aims at evaluating the robots’ ability to assess the level of discomfort that their presence might generate among humans. The 9280 samples in SocNav1 seem to be enough for machine learning purposes given the relatively small size of the data structures describing the scenarios. Furthermore, SocNav1 is particularly well-suited to be used to benchmark non-Euclidean machine learning algorithms such as graph neural networks. This paper describes the proposed dataset and the method employed to gather the data. To provide a further understanding of the nature of the dataset, an analysis and validation of the collected data are also presented

Análisis diferencial de las alteraciones genéticas presentes en el tumor primario "versus" metástasis del cáncer de mama hormonopositivo

A pesar de la heterogeneidad del cáncer de mama receptor hormonal positivo (CMRHP), aun no se ha establecido ninguna estratificación clínica significativa basada en los genes que con mayor frecuencia presentan mutación en esta enfermedad (TP53- PIK3CA-PTEN). Además, se desconoce la estabilidad del paisaje mutagénico desde las lesiones primarias hasta las metastásicas. Las Sociedades Internacionales han secuenciado las mutaciones de casos tempranos de diferentes subtipos de cáncer de mama. En esta tesis proponemos como hipótesis que el análisis pareado de las alteraciones genéticas presentes en tumores metastásicos en comparación con sus tumores primarios nos permitiría responder a: 1) si los casos de recurrencia conllevan un único paisaje genómico; 2) si en la metástasis este paisaje se preserva globalmente o no, y cuál es el papel de la frecuencia de alelos menores (MAF) en la expansión del cáncer. En este estudio, sobre las lesiones primarias y metastásicas de 11 casos de cáncer de mama pareados (43% estadios II, 57% en estadio III) y en 11 líneas celulares se realizaron análisis de secuenciación genética masiva de nueva generación (NGS) y análisis de arrays de CGH con un panel que cubre los genes mutados en el ≥1% de los casos de CMRHP, a más de 800X de profundidad. Los principales hallazgos mutacionales, basados en la frecuencia de las alteraciones presentes en las muestras, la expansión de las frecuencia de alelos menores (MAF) presentes en las muestras metastásicas y la severidad de los cambios, fueron validados con los datos procedentes del Atlas De Genoma del Cáncer de Mama (TCGA). La función de los genes pronósticos encontrados fue estudiada mediante modelos in vitro en líneas celulares de cáncer de mama hormonoresistentes..