Proposal for the creation of a Center for Learning Resources (CRA) in the School of San Lorenzo de Tarrazu

Education is the basis for economic and social development, but there are great inequalities in education and access to documentary resources, audiovisual and technology, a situation that affects school performance. The Organization of the United Nations Educational and Scientific Organization (UNESCO) found a correlation between levels of inequality in a country and performance: the greater the inequality, the worse the performance. Investment in education affects human development and benefit is obtained for the individual and society, which is necessary to ensure social equity, so that there is quality education for all. One of the fundamental purposes of the educational process is to train Costa Rican human thinking, analytical and critical of their environment. The purpose of that is acquired through various methods of academic achievement, learning, participation and constant communication of knowledge between the administrative staff, faculty and students. It is appropriate for schools and colleges have a school library or Resource Center for Learning, it is the gathering, analysis and work of the educational community, working with the intellectual growth of students, faculty, staff and community through access to different services and learning resources provided by the library or CRA.

Ergonomics as authoritarian or libertarian: Learning from colin ward's politics of design

Ergonomics is intrinsically connected to political debates about the good society, about how we should live. This article follows the ideas of Colin Ward by setting the practices of ergonomics and design along a spectrum between more libertarian approaches and more authoritarian. Within Anglo-American ergonomics, more authoritarian approaches tend to prevail, often against the wishes of designers who have had to fight with their employers for best possible design outcomes. The article draws on debates about the design and manufacturing of schoolchildren's furniture. Ergonomics would benefit from embracing these issues to stimulate a broader discourse amongst its practitioners about how to be open to new disciplines, particularly those in the social sciences.

e-Math Workshops : a forum for exchanging experiences of mathematics e-learning at university level

We report here about a series of international workshops on e-learning of mathematics at university level, which have been jointly organized by the three publicly funded open universities in the Iberian Peninsula and which have taken place annually since 2009. The history, achievements and prospects for the future of this initiative will be addressed.

Cooperative learning and its influences on the diminishing of the digital divide

Digital divide is an issue that concerns our technology dominated society. The parents of ubiquitous computing dreamt of a total proliferation of information technology. But the reality we live in is not yet prepared for this future. There is current a need to develop programs in order to diminish this difference between the digitally included and the excluded one. PROEJA-Transiarte is a project ran by Universidade de Brasília in the city of Ceilândia, Federal District of Brazil. It proposes a different approach on the issue of digital divide, by introducing the cooperative creation of cyberart, based on the life stories of each participant, into the regular curriculum of EJA (Educação de Jovens e Adultos) classes, thus implementing the concept of solidary education. This research project investigated the role played by the cooperative learning the students put in practice during the workshops of the project in the diminishing of the digital exclusion a great part of the students feel. It looked into their activities, analyzing the development of their cooperation, putting it next in the context of the digital and social inclusion. After a multi-dimensional research on the theme, in the context of PROEJA-Transiarte, the conclusion shows the impact cooperative learning has in the reduction of the digital divide, analyzing the perception of the currently involved students, the researchers active in the project, or the former students that had their lives improved because of the workshops they participated in.

Real-time audio interaction in serious games for music learning

In this LBD, we present several Apps for playing while learning music or for learning music while playing. The core of all the games is based on the good performance of the real-time audio interaction algorithms developed by the ATIC group at Universidad de Ma ́laga (SPAIN).

Guidelines for Creating ICT-based Adaptable Learning Resources

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

The development of selective copying: children’s learning from an expert versus their mother

This study tested the prediction that, with age, children should rely less on familiarity and more on expertise in their selective social learning. Experiment 1 (N=50) found that 5- to 6-year-olds copied the technique their mother used to extract a prize from a novel puzzle box, in preference to both a stranger and an established expert. This bias occurred despite children acknowledging the expert model’s superior capability. Experiment 2 (N=50) demonstrated a shift in 7-to 8-year-olds towards copying the expert. Children aged 9- to 10-years did not copy according to a model bias. The findings of a follow-up study (N=30) confirmed that, instead, they prioritized their own – partially flawed – causal understanding of the puzzle box.

Computational creativity: an interdisciplinary approach to sequential learning and creative generations

Creativity seems mysterious; when we experience a creative spark, it is difficult to explain how we got that idea, and we often recall notions like ``inspiration" and ``intuition" when we try to explain the phenomenon. The fact that we are clueless about how a creative idea manifests itself does not necessarily imply that a scientific explanation cannot exist. We are unaware of how we perform certain tasks, such as biking or language understanding, but we have more and more computational techniques that can replicate and hopefully explain such activities. We should understand that every creative act is a fruit of experience, society, and culture. Nothing comes from nothing. Novel ideas are never utterly new; they stem from representations that are already in mind. Creativity involves establishing new relations between pieces of information we had already: then, the greater the knowledge, the greater the possibility of finding uncommon connections, and the more the potential to be creative. In this vein, a beneficial approach to a better understanding of creativity must include computational or mechanistic accounts of such inner procedures and the formation of the knowledge that enables such connections. That is the aim of Computational Creativity: to develop computational systems for emulating and studying creativity. Hence, this dissertation focuses on these two related research areas: discussing computational mechanisms to generate creative artifacts and describing some implicit cognitive processes that can form the basis for creative thoughts.

Concepts and methods for efficient decentralized learning in federated settings

Deep Neural Networks (DNNs) have revolutionized a wide range of applications beyond traditional machine learning and artificial intelligence fields, e.g., computer vision, healthcare, natural language processing and others. At the same time, edge devices have become central in our society, generating an unprecedented amount of data which could be used to train data-hungry models such as DNNs. However, the potentially sensitive or confidential nature of gathered data poses privacy concerns when storing and processing them in centralized locations. To this purpose, decentralized learning decouples model training from the need of directly accessing raw data, by alternating on-device training and periodic communications. The ability of distilling knowledge from decentralized data, however, comes at the cost of facing more challenging learning settings, such as coping with heterogeneous hardware and network connectivity, statistical diversity of data, and ensuring verifiable privacy guarantees. This Thesis proposes an extensive overview of decentralized learning literature, including a novel taxonomy and a detailed description of the most relevant system-level contributions in the related literature for privacy, communication efficiency, data and system heterogeneity, and poisoning defense. Next, this Thesis presents the design of an original solution to tackle communication efficiency and system heterogeneity, and empirically evaluates it on federated settings. For communication efficiency, an original method, specifically designed for Convolutional Neural Networks, is also described and evaluated against the state-of-the-art. Furthermore, this Thesis provides an in-depth review of recently proposed methods to tackle the performance degradation introduced by data heterogeneity, followed by empirical evaluations on challenging data distributions, highlighting strengths and possible weaknesses of the considered solutions. Finally, this Thesis presents a novel perspective on the usage of Knowledge Distillation as a mean for optimizing decentralized learning systems in settings characterized by data heterogeneity or system heterogeneity. Our vision on relevant future research directions close the manuscript.

Applying machine learning: a multi-role perspective

Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.

Evaluating the Impact of Recommender Systems to Society

Nowadays, Recommender systems play a key role in managing information overload, particularly in areas such as e-commerce, music and cinema. However, despite their good-natured goal, in recent years there has been a growing awareness of their involvement in creating unwanted effects on society, such as creating biases of popularity or filter bubble. This thesis is an attempt to investigate the role of RS and its stakeholders in creating such effects. A simulation study will be performed using EcoAgent, an RL-based multi-stakeholder recommendation system, in a simulation environment that captures key user interactions, suppliers and the recommender system in order to identify possible unhealthy scenarios for stakeholders. In particular, we focus on analyzing the document catalog to see how the diversity of topics that users have access to varies during interactions. Finally, some post-processing methods will be defined on EcoAgent, one reactive and one proactive, which allows us to manipulate the agent’s behavior in order to study whether and how the topic distribution of documents is affected by content providers and by the fairness of the system.

The Value Of The 2005 International Society Of Urological Pathology (isup) Modified Gleason Grading System As A Predictor Of Biochemical Recurrence After Radical Prostatectomy.

To compare time and risk to biochemical recurrence (BR) after radical prostatectomy of two chronologically different groups of patients using the standard and the modified Gleason system (MGS). Cohort 1 comprised biopsies of 197 patients graded according to the standard Gleason system (SGS) in the period 1997/2004, and cohort 2, 176 biopsies graded according to the modified system in the period 2005/2011. Time to BR was analyzed with the Kaplan-Meier product-limit analysis and prediction of shorter time to recurrence using univariate and multivariate Cox proportional hazards model. Patients in cohort 2 reflected time-related changes: striking increase in clinical stage T1c, systematic use of extended biopsies, and lower percentage of total length of cancer in millimeter in all cores. The MGS used in cohort 2 showed fewer biopsies with Gleason score ≤ 6 and more biopsies of the intermediate Gleason score 7. Time to BR using the Kaplan-Meier curves showed statistical significance using the MGS in cohort 2, but not the SGS in cohort 1. Only the MGS predicted shorter time to BR on univariate analysis and on multivariate analysis was an independent predictor. The results favor that the 2005 International Society of Urological Pathology modified system is a refinement of the Gleason grading and valuable for contemporary clinical practice.

The Intrahippocampal Infusion Of Crotamine From Crotalus Durissus Terrificus Venom Enhances Memory Persistence In Rats.

Previous research has shown that crotamine, a toxin isolated from the venom of Crotalus durissus terrificus, induces the release of acetylcholine and dopamine in the central nervous system of rats. Particularly, these neurotransmitters are important modulators of memory processes. Therefore, in this study we investigated the effects of crotamine infusion on persistence of memory in rats. We verified that the intrahippocampal infusion of crotamine (1 μg/μl; 1 μl/side) improved the persistence of object recognition and aversive memory. By other side, the intrahippocampal infusion of the toxin did not alter locomotor and exploratory activities, anxiety or pain threshold. These results demonstrate a future prospect of using crotamine as potential pharmacological tool to treat diseases involving memory impairment, although it is still necessary more researches to better elucidate the crotamine effects on hippocampus and memory.

Diagnosis, Treatment, And Follow-up Of Medullary Thyroid Carcinoma: Recommendations By The Thyroid Department Of The Brazilian Society Of Endocrinology And Metabolism.

Medullary thyroid carcinoma (MTC) originates in the thyroid parafollicular cells and represents 3-4% of the malignant neoplasms that affect this gland. Approximately 25% of these cases are hereditary due to activating mutations in the REarranged during Transfection (RET) proto-oncogene. The course of MTC is indolent, and survival rates depend on the tumor stage at diagnosis. The present article describes clinical evidence-based guidelines for the diagnosis, treatment, and follow-up of MTC. The aim of the consensus described herein, which was elaborated by Brazilian experts and sponsored by the Thyroid Department of the Brazilian Society of Endocrinology and Metabolism, was to discuss the diagnosis, treatment, and follow-up of individuals with MTC in accordance with the latest evidence reported in the literature. After clinical questions were elaborated, the available literature was initially surveyed for evidence in the MedLine-PubMed database, followed by the Embase and Scientific Electronic Library Online/Latin American and Caribbean Health Science Literature (SciELO/Lilacs) databases. The strength of evidence was assessed according to the Oxford classification of evidence levels, which is based on study design, and the best evidence available for each question was selected. Eleven questions corresponded to MTC diagnosis, 8 corresponded to its surgical treatment, and 13 corresponded to follow-up, for a total of 32 recommendations. The present article discusses the clinical and molecular diagnosis, initial surgical treatment, and postoperative management of MTC, as well as the therapeutic options for metastatic disease. MTC should be suspected in individuals who present with thyroid nodules and family histories of MTC, associations with pheochromocytoma and hyperparathyroidism, and/or typical phenotypic characteristics such as ganglioneuromatosis and Marfanoid habitus. Fine-needle nodule aspiration, serum calcitonin measurements, and anatomical-pathological examinations are useful for diagnostic confirmation. Surgery represents the only curative therapeutic strategy. The therapeutic options for metastatic disease remain limited and are restricted to disease control. Judicious postoperative assessments that focus on the identification of residual or recurrent disease are of paramount importance when defining the follow-up and later therapeutic management strategies.

[renal Tumors: The International Society Of Urologic Pathology (isup) 2012 Consensus Conference Recommendations].

During the last 30 years many advances have been made in kidney tumor pathology. In 1981, 9 entities were recognized in the WHO Classification. In the latest classification of 2004, 50 different types have been recognized. Additional tumor entities have been described since and a wide variety of prognostic parameters have been investigated with variable success; however, much attention has centered upon the importance of features relating to both stage and grade. The International Society of Urological Pathology (ISUP) recommends after consensus conferences the development of reporting guidelines, which have been adopted worldwide ISUP undertook to review all aspects of the pathology of adult renal malignancy through an international consensus conference to be held in 2012. As in the past, participation in this consensus conference was restricted to acknowledged experts in the field.