The role of competencies and interests in developing complex IT-artefacts: the case of a metering system.

In this paper we aim at contributing to the ongoing debate on the relationship between artefacts and organizational structuration. Current literature emphasises the role of artefacts as mediators between interests of different categories of actors, namely between designers and users. Alternatively, it concentrates on the processes of learning and interacting between each actor and the artefacts themselves. We explore an arrangement which is not captured by these characterizations, and yet is becoming more and more common, that is situations in which complexity imposes an integration of different actors focusing on knowledge domains which are only partly overlapping. To explore these issues, we examine the dynamics surrounding the design of a complex artefact: an electronic metering system developed by a consortium of firms. The main results emerging from the case study are 1) the relevance of each actor's interests as the main rationale for explaining the technical features of the artefact; 2) the role of negotiation and consensus in determining the final shape of the artefact in term of its features; 3) the bundling/unbundling of features within the physical object as the cooperative effort rises/falls.artefacts; interests; ambiguity; competencies

Enabling an Open Data Ecosystem

Over the last decades, the interest in open data has increased dramatically in line with the improvements of information and communication technologies. Attention of institutions and private organizations focused on the value of the public sector information. Scholars and practitioners state that open data might have a huge impact in terms of efficiency within the public sector, social and economic wellbeing and might improve transparency and participation of people. While this is true, open data shows some issues that needs to be addressed. Among others, the most important are the technical quality of the published data and the sustainability over time of the whole ecosystem. Both issues are intertwined as actors providing services to the users need to both 1) assure that data is correct and 2) achieve economic sustainability. In such a market, an important role is growingly played by the enabler i.e. those actors that provide the technical infrastructure which allows for the sharing, linking and re-use of data. As the open data market is at its infancy, a survey of the market shows that such actors are very different in terms of nature and business models

Rationality, Autonomy and Coordination: the Sunk Costs Perspective

Our thesis is that an agent1 is autonomous only if he is capable, within a non predictable environment, to balance two forms of rationality: one that, given goals and preferences, enables him to select the best course of action (means-ends), the other, given current achievements and capabilities, enables him to adapt preferences and future goals. We will propose the basic elements of an economic model that should explain how and why this balance is achieved: in particular we underline that an agent’s capabilities can often be considered as partially sunk investments. This leads an agent, while choosing, to consider not just the value generated by the achievement of a goal, but also the lost value generated by the non use of existing capabilities.We will propose that, under particular conditions, an agent, in order to be rational, could be led to perform a rationalization process of justification that changes preferences and goals according to his current state and available capabilities. Moreover, we propose that such a behaviour could offer a new perspective on the notion of autonomy and on the social process of coordination

Bibliografía ictiológica del Delta del Paraná

Fil: Nadalin, Diego Oscar. División Zoología Vertebrados. Facultad de Ciencias Naturales y Museo. Universidad Nacional de La Plata; ArgentinaFil: Ponte Gómez, Justina. División Zoología Vertebrados. Facultad de Ciencias Naturales y Museo. Universidad Nacional de La Plata; ArgentinaFil: López, Hugo Luis. División Zoología Vertebrados. Facultad de Ciencias Naturales y Museo. Universidad Nacional de La Plata; Argentin

Peces continentales de la Argentina: Bibliografía. Brycon orbignyanus.

The goal of this work is to compile the existing information about the species present in our country. This has been done by means of datasheets that list both local references and reviews by foreign authors that include Argentine taxa. The main information sources consulted were Ringuelet et al. (1967), CLOFFSCA (2003), López et al. (2003; 2006), Liotta (2006) and the online databases of W. N. Eschmeyer and Fish Base. This is an open-ended publication. As such, it will require permanent updating, which will depend on the good will and collaboration of the ichthyological community. With this contribution, we hope to help to build a database of the freshwater fish of Argentina. The completion of this project will provide support to diverse plans emanating from different sectors, as well as promote the diffusion of this field of research and reaffirm Argentina’s sovereign rights over our natural resources. (PDF tiene 9 paginas.

Rediseño de identidad corporativa y la percepción visual de los estudiantes de la I.E Gastón María, SJM, Lima – 2022

En esta presente investigación fue determinar la relación que existe entre nuestras dos variables que son identidad corporativa y percepción visual de los estudiantes de la institución Gastón María, para ello se realizó un manual de identidad corporativa. En cuanto a la metodología se utilizó un enfoque cuantitativo, de tipo aplicada con un diseño no experimental y nivel correlacional. La población estuvo conformada por 170 alumnos, donde el tamaño de nuestra muestra fue de 118 alumnos. Asimismo, se aplicó la técnica de la encuesta que estuvo conformada por 14 ítems, según la escala de Likert, donde fue validado por 3 expertos del tema, es por ello que se realizó nuestro alfa de Cronbach para poder obtener la fiabilidad del instrumento, donde obtuvo como resultado de 0,931 por lo tanto nuestro instrumento tiene una muy alta confiablidad. De igual manera nuestros resultados obtenidos del trabajo de investigación tuvieron un nivel de significancia de 0,760 teniendo una correlación de alta confiabilidad por lo tanto se rechaza la hipótesis nula y se acepta la hipótesis de investigación, por lo tanto, existe una buena relación entre la variable identidad corporativa y percepción visual

Aspectos neurodesenvolvimentais do transtorno bipolar em uma coorte populacional de nascimento

Mundialmente, o Transtorno Bipolar (TB) é sexta causa de incapacidade. Entre os primeiros sintomas de humor e o diagnóstico formal, as pessoas com TB demoram cerca de seis anos para receber o tratamento adequado. Assim, objetivou-se desenvolver um modelo preditivo de indivíduos que desenvolverão TB aos 22 anos de idade usando algoritmos de inteligência artificial (machine learning). Foram acompanhadas 3.748 pessoas ao nascer e aos 11, 15, 18 e 22 anos de idade em uma coorte de nascimentos da cidade de Pelotas, RS, Brasil. Utilizou-se o algoritmo elastic net com 10-fold cross- validation para predizer quais indivíduos desenvolverão TB aos 22 anos de idade, usando as variáveis coletadas do nascimento até aos 18 anos de idade. Posteriormente, foi desenvolvido um modelo de estratificação de risco de pessoas com TB. Um total de 107 (2,8%) indivíduos foi diagnosticado com TB tipo I (TB-I), 26 (0.6%) participantes com o tipo II (TB-II) e 87 (2,3%) pessoas com o tipo não-especificado. O modelo com as variáveis coletadas aos 18 anos de idade foi o que alcançou melhores medidas de desempenho: área sob a curva ROC (AUC) de 0,82 (95% IC, 0,75– 0,88), acurácia balanceada de 0,75, sensibilidade de 0,72 e especificidade de 0,77. As variáveis mais importantes foram risco de suicídio, transtorno de ansiedade generalizada e abuso físico parental. Além disso, o subgrupo com alto risco para TB apresentou uma alta freqüência para consumo de drogas e sintomas depressivos. A detecção precoce de TB usando variáveis clínicas e sociodemográficas pode ser clinicamente relevante para intervir precocemente e prevenir o curso pernicioso do transtorno. O quociente de inteligência (QI) e o número de reprovações escolares podem ser importantes marcadores clínicos de neurodesenvolvimento para identificação do TB e essa associação permanece controversa na literatura. Objetivou-se identificar o QI e o número de reprovações escolares como fatores de risco para TB antes do diagnóstico formal em um estudo de coorte de nascimentos. Foi incluído 3580 participantes do estudo de coorte de nascimentos de base populacional de Pelotas na coleta de dados aos 22 anos e, na coleta anterior, nenhum sujeito deveria ter diagnóstico prévio de transtorno de humor. Foi realizado modelos de regressão controlando potenciais confundidores para avaliar o impacto do QI e do número de reprovações escolares obtido aos 18 anos em um diagnóstico subsequente de TB e Transtorno Depressivo Maior (TDM) aos 22 anos, comparando indivíduos sem transtornos de humor como comparadores. Encontrou-se que ter um QI baixo e limítrofe (abaixo de 70) aos 18 anos foi um marcador de risco para participantes com TB (Razão de Chance Ajustado [AOR] 1,75, IC 95%: 1,00–3,09, p<0,05) e QI superior (acima de 120) para indivíduos com TDM (AOR 2,16, IC 95%: 1,24–3,75, p<0,001). O número de reprovações escolares aumentou o risco de TB (AOR 1,23, IC 95%: 1,11–1,41, p<0,001), mas não para indivíduos com TDM. O número de reprovações escolares foi um significativo marcador para TB-I (AOR 1,36, IC 95%: 1,17–1,58, p<0,001), porém não em indivíduos com TB-II ou sem transtorno de humor. Os resultados sugerem o TB tem um desempenho intelectual pré-mórbido característico. Estes achados podem contribuir para a compreensão da fisiopatologia do TB e seu curso neurodesenvolvimental, auxiliando no desenvolvimento de ferramentas para sua detecção precoce.Bipolar Disorder (BD) is the sixth leading cause of disability worldwide. It takes about six years for people with BD to receive adequate treatment. Thus, the objective was to develop a predictive model of individuals who will develop BD at 22 years of age using data from a birth cohort through machine learning algorithms. A total of 3,748 participants were followed at birth and 11, 15, 18, and 22 years of age. The elastic net algorithm with 10-fold cross-validation was used to predict which individuals will develop BD at 22 years of age, using variables collected from birth to age of 18 years. Subsequently, a risk stratification model for subjects with BD was developed. A total of 107 (2.8%) individuals were diagnosed with BD type I (BD-I), 26 (0.6%) participants with type II (BD-II), and 87 (2.3%) people with type not otherwise specified. The model with the variables collected at 18 years of age was the one that achieved the best performance measures: area under the ROC curve (AUC) of 0.82 (95% CI, 0.75–0.88), balanced accuracy of 0.75, sensitivity of 0.72, and specificity of 0.77. The most important variables were suicide risk, generalized anxiety disorder, and parental physical abuse. In addition, the subgroup at high risk for TB had a high frequency of drug use and depressive symptoms. Early detection of TB utilizing clinical and sociodemographic variables may be clinically relevant to intervene early and prevent the pernicious course of the disorder. The intelligence quotient (IQ) and the number of school failures may be important clinical neurodevelopmental markers for identifying BD. This association remains controversial in the literature. The objective was to identify IQ and the number of school failures as risk factors for BD before formal diagnosis in a birth cohort study. A total of 3580 participants from the Pelotas population-based birth cohort study were included in the data collection at the age of 22 years, and no subject should have had a previous diagnosis of mood disorder in a previous follow-up visit. Regression models controlling for potential confounders were performed to assess the impact of IQ and the number of school failures obtained at age 18 on a diagnosis of BD and Major Depressive Disorder (MDD) at age 22, comparing individuals without mood disorders. Having a low and borderline IQ (below 70) at age 18 was a risk marker for participants with BD (Adjusted Odds Ratio [AOR] 1.75, 95% CI: 1.00–3.09, p<0.05) and higher IQ (above 120) for individuals with MDD (AOR 2.16, 95% CI: 1.24–3.75, p<0.001). The number of school failures increased the risk for BD (AOR 1.23, 95% CI: 1.11–1.41, p<0.001), but not for individuals with MDD. The number of school failures was a significant marker for BD-I (AOR 1.36, 95% CI: 1.17–1.58, p<0.001), but not in individuals with BD-II or without a mood disorder. The results suggest that BD has a characteristic premorbid intellectual performance. These findings may contribute to understanding the pathophysiology of BD and its neurodevelopmental course, aiding in developing tools for early detection

Preditores de heterogeneidade cognitiva no transtorno bipolar : uma abordagem machine-learning

Objetivos: Identificar os preditores de heterogeneidade cognitiva nos sujeitos com Transtorno Bipolar (TB). Métodos: Foi recrutado 142 sujeitos com TB em atendimento ambulatorial e 100 voluntários sem transtornos psiquiátricos do Brasil e da Espanha para realizar avaliação neuropsicológica. Foi realizado Análise de Cluster Hierárquica e Análise de Função Discriminante para determinar e confirmar os subgrupos cognitivos. Por fim, foi usado o algoritmo Classification and Regression Tree (CART) para identificar os preditores dos subgrupos cognitivos anteriormente estabelecidos. Resultados: Foi observado a presença de três clusters cognitivos: indivíduos cognitivamente intacto (38%), seletivamente prejudicados (38%) e globalmente prejudicados (21%). Os preditores mais importantes foram anos de educação, anos de doença, número de hospitalizações, idade e idade de início. Conclusão: Os resultados corroboram com recentes achados sobre a heterogeneidade cognitiva nos sujeitos com TB. Além disso, os presentes achados indicam uma sobreposição entre aspectos neurodesenvolvimentais e história de doença.Objective: We aimed to determine predictors of cognitive heterogeneity in subjects with Bipolar Disorder (BD). Methods: We recruited 142 outpatients with Bipolar Disorder and 100 unaffected volunteers from Brazil and Spain that underwent a neuropsychological assessment. We performed Hierarchical Cluster Analysis and Discriminant Function Analysis to identify and validate cognitive subgroups, respectively. Then, we used Classification and Regression Tree (CART) algorithm to determine predictors of the cognitive clusters. Results: We identified three cognitive clusters in BD: intact (38%), selectively impaired (38%), and globally impaired subjects (21%). The most important predictors of cognitive subgroups were years of education, years of disease, the number of hospitalizations, age, and age of onset, respectively. Conclusion: These results corroborate with recent findings of neuropsychological heterogeneity in Bipolar Disorder. Furthermore, the present findings suggest overlapping between neurodevelopmental and morbid aspects