47 research outputs found
Assessing the Effectiveness of Sequence Diagrams in the Comprehension of Functional Requirements: Results from a Family of Five Experiments
Modeling is a fundamental activity within the requirements engineering process and concerns the construction of abstract descriptions of requirements that are amenable to interpretation and validation. The choice of a modeling technique is critical whenever it is necessary to discuss the interpretation and validation of requirements. This is particularly true in the case of functional requirements and stakeholders with divergent goals and different backgrounds and experience. This paper presents the results of a family of experiments conducted with students and professionals to investigate whether the comprehension of functional requirements is influenced by the use of dynamic models that are represented by means of the UML sequence diagrams. The family contains five experiments performed in different locations and with 112 participants of different abilities and levels of experience with the UML. The results show that sequence diagrams improve the comprehension of the modeled functional requirements in the case of high ability and more experienced participants
Enabling the Reuse of Stored Model Transformations Through Annotations
International audienceWith the increasing adoption of MDE, model transformations , one of its core concepts together with metamodeling, stand out as a valuable asset. Therefore, a mechanism to annotate and store existing model transformations appears as a critical need for their efficient exploitation and reuse. Unfortunately, although several reuse mechanisms have been proposed for software artifacts in general and models in particular , none of them is specially tailored to the domain of model transformations. In order to fill this gap, we present here such a mechanism. Our approach is composed by two elements 1) a new DSL specially conceived for describing model transformations in terms of their functional and non-functional properties 2) a semi-automatic process for annotating and querying (repositories of) model transformations using as criteria the properties of our DSL. We validate the feasibility of our approach through a prototype implementation that integrates our approach in a GitHub repository
Exploring quality-aware architectural transformations at run-time: the ENIA case
Adapting software systems at run-time is a key issue, especially when these systems consist of components used as intermediary for human-computer interaction. In this sense, model transformation techniques have a widespread acceptance as a mechanism for adapting and evolving the software architecture of such systems. However, existing model transformations often focus on functional requirements, and quality attributes are only manually considered after the transformations are done. This paper aims to improve the quality of adaptations and evolutions in component-based software systems by taking into account quality attributes within the model transformation process. To this end, we present a quality-aware transformation process using software architecture metrics to select among many alternative model transformations. Such metrics evaluate the quality attributes of an architecture. We validate the presented quality-aware transformation process in ENIA, a geographic information system whose user interfaces are based on coarsegrained components and need to be adapted at run-time
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In vitro approaches to assess the effects of açai (Euterpe oleracea) digestion on polyphenol availability and the subsequent impact on the faecal microbiota
A considerable proportion of dietary plant-polyphenols reach the colon intact; determining the effects of these compounds on colon-health is of interest. We hypothesise that both fibre and plant polyphenols present in açai (Euterpe oleracea) provide prebiotic and anti-genotoxic benefits in the colon. We investigated this hypothesis using a simulated in vitro gastrointestinal digestion of açai pulp, and a subsequent pH-controlled, anaerobic, batch-culture fermentation model reflective of the distal region of the human large intestine.
Following in vitro digestion, 49.8% of the total initial polyphenols were available. In mixed-culture fermentations with faecal inoculate, the digested açai pulp precipitated reductions in the numbers of both the Bacteroides-Prevotella spp. and the Clostridium-histolyticum groups, and increased the short-chain fatty acids produced compared to the negative control. The samples retained significant anti-oxidant and anti-genotoxic potential through digestion and fermentation.
Dietary intervention studies are needed to prove that consuming açai is beneficial to gut health
Asociación entre bajo peso al nacer y malformaciones congénitas
Introducción: Las anomalías congénitas son defectos estructurales o funcionales durante la vida
intrauterina. Es poco conocida la relación existente entre el bajo peso al nacer y la predisposición a una
anomalía congénita. Objetivo: Evaluar la asociación entre el bajo peso al nacer y la manifestación de anomalías congénitas en neonatos. Métodos: Se realizó un estudio transversal. La población de estudio fueron madres que dieron a luz a neonatos en un hospital de Asunción, Paraguay, en 2018. Se crearon fichas de recolección de datos con las características maternas y neonatales. La variable desenlace fue malformaciones congénitas al nacimiento. La variable exposición fue bajo peso al nacer, definido como el reporte clínico de peso menor a 2 500 gramos en un neonato.
Resultados: De 225 mujeres, se encontró que el 26,7 % presentó infecciones de transmisión maternoneonatal (60/165); 102 (45,3 %) fueron prematuros y 79 (35,1 %) presentaron malformaciones
congénitas. Se evidenció asociación positiva entre antecedente de bajo peso al nacer y malformaciones
congénitas (RP= 2,32; IC 95 %: 1,68-3,20).
Conclusiones: Se evidencia una asociación positiva entre el antecedente de bajo peso al nacer y la
presencia de malformaciones congénitas.Campus Lima Centr
Global overview of the management of acute cholecystitis during the COVID-19 pandemic (CHOLECOVID study)
Background: This study provides a global overview of the management of patients with acute cholecystitis during the initial phase of the COVID-19 pandemic. Methods: CHOLECOVID is an international, multicentre, observational comparative study of patients admitted to hospital with acute cholecystitis during the COVID-19 pandemic. Data on management were collected for a 2-month study interval coincident with the WHO declaration of the SARS-CoV-2 pandemic and compared with an equivalent pre-pandemic time interval. Mediation analysis examined the influence of SARS-COV-2 infection on 30-day mortality. Results: This study collected data on 9783 patients with acute cholecystitis admitted to 247 hospitals across the world. The pandemic was associated with reduced availability of surgical workforce and operating facilities globally, a significant shift to worse severity of disease, and increased use of conservative management. There was a reduction (both absolute and proportionate) in the number of patients undergoing cholecystectomy from 3095 patients (56.2 per cent) pre-pandemic to 1998 patients (46.2 per cent) during the pandemic but there was no difference in 30-day all-cause mortality after cholecystectomy comparing the pre-pandemic interval with the pandemic (13 patients (0.4 per cent) pre-pandemic to 13 patients (0.6 per cent) pandemic; P = 0.355). In mediation analysis, an admission with acute cholecystitis during the pandemic was associated with a non-significant increased risk of death (OR 1.29, 95 per cent c.i. 0.93 to 1.79, P = 0.121). Conclusion: CHOLECOVID provides a unique overview of the treatment of patients with cholecystitis across the globe during the first months of the SARS-CoV-2 pandemic. The study highlights the need for system resilience in retention of elective surgical activity. Cholecystectomy was associated with a low risk of mortality and deferral of treatment results in an increase in avoidable morbidity that represents the non-COVID cost of this pandemic
The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study
The use of e-learning in higher education has increased significantly in recent years, which has led to several studies being conducted to investigate the usability of the platforms that support it. A variety of different usability evaluation methods and attributes have been used, and it has therefore become important to start reviewing this work in a systematic way to determine how the field has developed in the last 15 years. This paper describes a systematic mapping study that performed searches on five electronic libraries to identify usability issues and methods that have been used to evaluate e-learning platforms. Sixty-one papers were selected and analysed, with the majority of studies using a simple research design reliant on questionnaires. The usability attributes measured were mostly related to effectiveness, satisfaction, efficiency, and perceived ease of use. Furthermore, several research gaps have been identified and recommendations have been made for further work in the area of the usability of online learning
On the Effectiveness of Dynamic Modeling in UML: Results from an External Replication
In this paper, we propose an automatic approach to group web pages that are similar at the content level. The approach uses the Levenshtein string edit distance and Latent Semantic Indexing to compute page dissimilarity and then groups them using iteratively a Graph-Theoretic clustering algorithm. To automate the clustering process a prototype has been implemented and used to assess the proposed approach on three web sites