Identifying Unmaintained Projects in GitHub

Background: Open source software has an increasing importance in modern software development. However, there is also a growing concern on the sustainability of such projects, which are usually managed by a small number of developers, frequently working as volunteers. Aims: In this paper, we propose an approach to identify GitHub projects that are not actively maintained. Our goal is to alert users about the risks of using these projects and possibly motivate other developers to assume the maintenance of the projects. Method: We train machine learning models to identify unmaintained or sparsely maintained projects, based on a set of features about project activity (commits, forks, issues, etc). We empirically validate the model with the best performance with the principal developers of 129 GitHub projects. Results: The proposed machine learning approach has a precision of 80%, based on the feedback of real open source developers; and a recall of 96%. We also show that our approach can be used to assess the risks of projects becoming unmaintained. Conclusions: The model proposed in this paper can be used by open source users and developers to identify GitHub projects that are not actively maintained anymore.Comment: Accepted at 12th International Symposium on Empirical Software Engineering and Measurement (ESEM), 10 pages, 201

Transthyretin familial amyloid polyneuropathy impact on health-related quality of life

info:eu-repo/semantics/publishedVersio

Machinery for artificial emotions

We present a preliminary definition and theory of artificial emotion viewed as a sequential process comprising the appraisal of the agent global state, the generation of an emotion-signal, and an emotion-response. This theory distinguishes cognitive from affective appraisal on an architecture-grounded basis. Affective appraisal is performed by the affective component of the architecture; cognitive appraisal is performed by its cognitive component. A scheme for emotion classification with seven dimensions is presented. Among them, we emphasize the roles played by emotions and the way these roles are fulfilled. It is shown how emotions are generated, represented, and used in the Salt & Pepper architecture for autonomous agents (Botelho, 1997). Salt & Pepper is a specific architecture comprising an affective engine, a cognitive and behavioral engine, and an interruption manager. Most properties of the cognitive and behavioral engine rely upon a hybrid associative, schema-based long-term memory. In Salt & Pepper, emotion-signals, represented by label, object of appraisal, urgency, and valence, are generated by the affective engine through the appraisal of the agent's global state. For each emotion-signal there are several nodes stored and interconnected in long-term memory. Each of these nodes contains an emotion response that may be executed when an emotion-signal is generated. Emotion intensity relates to the activation of the node. It is shown that the Salt & Pepper architecture for autonomous agents exhibits several properties usually related to emotion: state and mood congruence, compound emotions, autonomic emotion-responses, and different emotion-responses to the same stimulus including the generation of different motives. The implementation of a concrete example is described.info:eu-repo/semantics/acceptedVersio

Low back pain in adolescents : identification of psychological risk factors. Epidemiological study in Great Lisbon area

FCT (Fundação para a Ciência e a Tecnologia), IDP (Instituto do Desporto de Portugal), AIESEP World Congres

Growth-Driven Percolations: The Dynamics of Community Formation in Neuronal Systems

The quintessential property of neuronal systems is their intensive patterns of selective synaptic connections. The current work describes a physics-based approach to neuronal shape modeling and synthesis and its consideration for the simulation of neuronal development and the formation of neuronal communities. Starting from images of real neurons, geometrical measurements are obtained and used to construct probabilistic models which can be subsequently sampled in order to produce morphologically realistic neuronal cells. Such cells are progressively grown while monitoring their connections along time, which are analysed in terms of percolation concepts. However, unlike traditional percolation, the critical point is verified along the growth stages, not the density of cells, which remains constant throughout the neuronal growth dynamics. It is shown, through simulations, that growing beta cells tend to reach percolation sooner than the alpha counterparts with the same diameter. Also, the percolation becomes more abrupt for higher densities of cells, being markedly sharper for the beta cells.Comment: 8 pages, 10 figure

Fontes e freqüências de aplicação de nitrogênio via água de irrigação no mamoeiro.

A escassez ou má distribuição das chuvas no Nordeste e em outras regiões do Brasil, como o Centro Oeste, o Sudeste e o Sul torna obrigatório o uso da irrigação. A irrigação, por sua vez, tem trazido consigo a atividade de aplicação de adubos via água, ou a fertirrigação, que vem sendo usada em ritmo crescente de fruticultores. O nitrogênio (N) é o elemento requerido em maior quantidade, pelo mamoeiro seguido posteriormente pelo potássio (K) e pelo cálcio (Ca) conforme Cunha & Haag (1980) citado por Oliveira (2002). A dinâmica do N difere conforme a fonte, sendo que no caso das fontes amidicas e amoniacais o N ocorrerá no solo na forma de amônio inicialmente e de nitrato posteriormente; na forma nítrica, o N ocorrerá na forma de nitrato o que indica maior mobilidade do mesmo no solo com possibilidades inclusive de lixiviação.bitstream/item/50972/1/comunicado-111-1.pd