Utilização de agentes inteligentes e raciocínio baseado em casos no acompanhamento de uma seqüência de estudos coletivos

This paper presents the use of techniques of Artificial Intelligence in the accompaniment of the study of one disciplines. The first technique consists of the use of Intelligent Agents whose objective is to follow the work (study) of the pupil in an interface. The second technique is about the Based Case Reasoning, that through the information gotten for the agents, on the study of diverse pupils, identify possible imperfections of collective learning and as reply it suggests modifications so that the same ones reach one better form of assimilation of the content of discipline.Este artigo apresenta a utilização de técnicas de Inteligência Artificial no acompanhamento do estudo de uma disciplina. A primeira técnica consiste na utilização de Agentes Inteligentes cujo objetivo é acompanhar o trabalho (estudo) do aluno através de uma interface específica. A segunda técnica utilizada, Raciocínio Baseado em Casos, visa identificar possíveis falhas de aprendizado coletivo e como resposta propor modificações para que se alcance uma melhor forma de assimilação do conteúdo da disciplina.Eje: Tecnología Informática aplicada en Educación (TIE)Red de Universidades con Carreras en Informática (RedUNCI

Utilização de agentes inteligentes e raciocínio baseado em casos no acompanhamento de uma seqüência de estudos coletivos

This paper presents the use of techniques of Artificial Intelligence in the accompaniment of the study of one disciplines. The first technique consists of the use of Intelligent Agents whose objective is to follow the work (study) of the pupil in an interface. The second technique is about the Based Case Reasoning, that through the information gotten for the agents, on the study of diverse pupils, identify possible imperfections of collective learning and as reply it suggests modifications so that the same ones reach one better form of assimilation of the content of discipline.Este artigo apresenta a utilização de técnicas de Inteligência Artificial no acompanhamento do estudo de uma disciplina. A primeira técnica consiste na utilização de Agentes Inteligentes cujo objetivo é acompanhar o trabalho (estudo) do aluno através de uma interface específica. A segunda técnica utilizada, Raciocínio Baseado em Casos, visa identificar possíveis falhas de aprendizado coletivo e como resposta propor modificações para que se alcance uma melhor forma de assimilação do conteúdo da disciplina.Eje: Tecnología Informática aplicada en Educación (TIE)Red de Universidades con Carreras en Informática (RedUNCI

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ

LES DÉFIS DE LA CROISSANCE DE LA POPULATION URBAINE DANS LE CONTEXTE DES VILLES INTELLIGENTES

O crescimento populacional mundial e a respectiva concentração de grande parte destas pessoas nas áreas urbanas gera desafios para os gestores. Neste contexto, surgem as cidades inteligentes, que são definidas como um novo método para o desenvolvimento sustentável das cidades. Este artigo analisa as concepções conceituais quanto às cidades inteligentes comparado ao crescimento populacional urbano das cidades e discutindo se o processo de expansão territorial e a verticalização das cidades. A problemática desenvolvida procura discutir se de fato as cidades inteligentes são o caminho para o preparo do crescimento populacional. Os resultados mostram que há significativa hipótese para essa condição.The world population growth and the concentration of large numbers of these people in urban areas poses challenges for managers. In this context, intelligent cities emerge, which are defined as a new method for the sustainable development of cities. This article analyzes the conceptual conceptions regarding intelligent cities compared to the urban population growth of the cities and discusses the process of territorial expansion and the verticalization of cities. The problematic developed seeks to discuss whether in fact smart cities are the way to prepare population growth. The results show that there is a significant hypothesis for this condition.El crecimiento de la población mundial y su concentración de gran parte de estas personas en las zonas urbanas generan desafíos para los gestores. En este contexto, surgen las ciudades inteligentes, que se definen como un nuevo método para el desarrollo sostenible de las ciudades. Este artículo analiza las concepciones conceptuales en cuanto a las ciudades inteligentes comparado al crecimiento poblacional urbano de las ciudades y discutiendo el proceso de expansión territorial y la verticalización de las ciudades. La problemática desarrollada busca discutir si de hecho las ciudades inteligentes son el camino para la preparación del crecimiento poblacional. Los resultados muestran que hay una significativa hipótesis para esta condición.La croissance démographique mondiale et la concentration d'un grand nombre de ces personnes dans les zones urbaines posent des problèmes aux gestionnaires. Dans ce contexte, des villes intelligentes émergent, qui sont définies comme une nouvelle méthode de développement durable des villes. Cet article analyse les conceptions conceptuelles concernant les villes intelligentes par rapport à la croissance de la population urbaine des villes et examine le processus d'expansion territoriale et la verticalisation des villes. La problématique développée cherche à déterminer si ce sont les villes intelligentes qui préparent la croissance démographique. Les résultats montrent qu'il existe une hypothèse significative pour cette condition

Integrative Analysis of the Ethanol Tolerance of Saccharomyces cerevisiae.

Ethanol (EtOH) alters many cellular processes in yeast. An integrated view of different EtOH-tolerant phenotypes and their long noncoding RNAs (lncRNAs) is not yet available. Here, large-scale data integration showed the core EtOH-responsive pathways, lncRNAs, and triggers of higher (HT) and lower (LT) EtOH-tolerant phenotypes. LncRNAs act in a strain-specific manner in the EtOH stress response. Network and omics analyses revealed that cells prepare for stress relief by favoring activation of life-essential systems. Therefore, longevity, peroxisomal, energy, lipid, and RNA/protein metabolisms are the core processes that drive EtOH tolerance. By integrating omics, network analysis, and several other experiments, we showed how the HT and LT phenotypes may arise: (1) the divergence occurs after cell signaling reaches the longevity and peroxisomal pathways, with CTA1 and ROS playing key roles; (2) signals reaching essential ribosomal and RNA pathways via SUI2 enhance the divergence; (3) specific lipid metabolism pathways also act on phenotype-specific profiles; (4) HTs take greater advantage of degradation and membraneless structures to cope with EtOH stress; and (5) our EtOH stress-buffering model suggests that diauxic shift drives EtOH buffering through an energy burst, mainly in HTs. Finally, critical genes, pathways, and the first models including lncRNAs to describe nuances of EtOH tolerance are reported here

The value of open-source clinical science in pandemic response: lessons from ISARIC

International audienc

Implementation of Recommendations on the Use of Corticosteroids in Severe COVID-19

Importance: Research diversity and representativeness are paramount in building trust, generating valid biomedical knowledge, and possibly in implementing clinical guidelines. Objectives: To compare variations over time and across World Health Organization (WHO) geographic regions of corticosteroid use for treatment of severe COVID-19; secondary objectives were to evaluate the association between the timing of publication of the RECOVERY (Randomised Evaluation of COVID-19 Therapy) trial (June 2020) and the WHO guidelines for corticosteroids (September 2020) and the temporal trends observed in corticosteroid use by region and to describe the geographic distribution of the recruitment in clinical trials that informed the WHO recommendation. Design, setting, and participants: This prospective cohort study of 434 851 patients was conducted between January 31, 2020, and September 2, 2022, in 63 countries worldwide. The data were collected under the auspices of the International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC)-WHO Clinical Characterisation Protocol for Severe Emerging Infections. Analyses were restricted to patients hospitalized for severe COVID-19 (a subset of the ISARIC data set). Exposure: Corticosteroid use as reported to the ISARIC-WHO Clinical Characterisation Protocol for Severe Emerging Infections. Main outcomes and measures: Number and percentage of patients hospitalized with severe COVID-19 who received corticosteroids by time period and by WHO geographic region. Results: Among 434 851 patients with confirmed severe or critical COVID-19 for whom receipt of corticosteroids could be ascertained (median [IQR] age, 61.0 [48.0-74.0] years; 53.0% male), 174 307 (40.1%) received corticosteroids during the study period. Of the participants in clinical trials that informed the guideline, 91.6% were recruited from the United Kingdom. In all regions, corticosteroid use for severe COVID-19 increased, but this increase corresponded to the timing of the RECOVERY trial (time-interruption coefficient 1.0 [95% CI, 0.9-1.2]) and WHO guideline (time-interruption coefficient 1.9 [95% CI, 1.7-2.0]) publications only in Europe. At the end of the study period, corticosteroid use for treatment of severe COVID-19 was highest in the Americas (5421 of 6095 [88.9%]; 95% CI, 87.7-90.2) and lowest in Africa (31 588 of 185 191 [17.1%]; 95% CI, 16.8-17.3). Conclusions and relevance: The results of this cohort study showed that implementation of the guidelines for use of corticosteroids in the treatment of severe COVID-19 varied geographically. Uptake of corticosteroid treatment was lower in regions with limited clinical trial involvement. Improving research diversity and representativeness may facilitate timely knowledge uptake and guideline implementation

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use