A multi-criteria decision support system for a routing problem in waste collection

Autor proof

Defining risk acceptance criteria in occupational settings: A case study in the furniture industrial sector

The use of appropriate acceptance criteria in the risk assessment process for occupational accidents is an important issue but often overlooked in the literature, particularly when new risk assessment methods are proposed and discussed. In most cases, there is no information on how or by whom they were defined, or even how companies can adapt them to their own circumstances. Bearing this in mind, this study analysed the problem of the definition of risk acceptance criteria for occupational settings, defining the quantitative acceptance criteria for the specific case study of the Portuguese furniture industrial sector. The key steps to be considered in formulating acceptance criteria were analysed in the literature review. By applying the identified steps, the acceptance criteria for the furniture industrial sector were then defined. The Cumulative Distribution Function (CDF) for the injury statistics of the industrial sector was identified as the maximum tolerable risk level. The acceptable threshold was defined by adjusting the CDF to the Occupational, Safety & Health (OSH) practitioners’ risk acceptance judgement. Adjustments of acceptance criteria to the companies’ safety cultures were exemplified by adjusting the Burr distribution parameters. An example of a risk matrix was also used to demonstrate the integration of the defined acceptance criteria into a risk metric. This work has provided substantial contributions to the issue of acceptance criteria for occupational accidents, which may be useful in overcoming the practical difficulties faced by authorities, companies and experts.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Evolving hallmarks in urothelial bladder cancer: unveiling potential biomarkers

Urothelial bladder carcinoma (UBC), the most frequent type (90%) of bladder cancer and the second most common malignancy of the urogenital region, is a relatively well understood type of cancer, with numerous studies concerning pathogenetic pathways, natural history and bladder tumor biology being reported. Despite this, it continues to remain a challenge in the oncology field, mostly due to its relapsing and progressive nature, and to the heterogeneity in the response to cisplatin-containing regimens. Although the formulae based on clinical staging and histopathological parameters are classically used as diagnostic and prognostic tools, they have proven insufficient to characterize the individual biological features and clinical behaviour of the tumours. Understanding the pathobiology of the disease can add important information to these classical criteria, and contribute to accurately predict outcome and individualize therapy for UBC patients. In this line of investigation, we found that tumour angiogenesis and lymphangiogenesis, the process of invasion and metastasis and the energy metabolism reprogramming/tumour microenvironment encompass several potential biomarkers that seem to infl bladder cancer aggressiveness and chemoresistance. We particularly highlight the roles of lymphovascular invasion, and of RKIP, CD147 and MCT1 immunoexpressions, as relevant prognostic and/or predictive biomarkers, and as promising areas of therapeutic intervention, eliciting for the development of additional studies that can validate and further explore these biomarkers.

Development of a model for occupational risk acceptance criteria definition in industrial settings

Doctoral Dissertation for PhD degree in Industrial and Systems Engineering

Macroscopic and histopathological study of the placenta: an essential resource in litigation processes

The pathological study of the placenta is of upmost importance in cases of unexplained fetal/perinatal loss and often these carry litigation implications. Integrating pathological findings and the underlying pathophysiological processes, leading to placental lesions, is fundamental for the evaluation of poor fetal and perinatal outcomes and to distinguish from cases of true negligence.