Bone turnover markers for early detection of fracture healing disturbances: A review of the scientific literature

Imaging techniques are the standard method for assessment of fracture healing processes. However, these methods are perhaps not entirely reliable for early detection of complications, the most frequent of these being delayed union and non-union. A prompt diagnosis of such disorders could prevent prolonged patient distress and disability. Efforts should be directed towards the development of new technologies for improving accuracy in diagnosing complications following bone fractures. The variation in the levels of bone turnover markers (BTMs) have been assessed with regard to there ability to predict impaired fracture healing at an early stage, nevertheless the conclusions of some studies are not consensual. In this article the authors have revised the potential of BTMs as early predictors of prognosis in adult patients presenting traumatic bone fractures but who did not suffer from osteopenia or postmenopausal osteoporosis. The available information from the different studies performed in this field was systematized in order to highlight the most promising BTMs for the assessment of fracture healing outcome.

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

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A decision support system for a waste collection vehicle routing problem

The selective collection of municipal solid waste for recycling is a very complex and expensive process, where a major issue is to perform cost-efficient waste collection routes. Despite the abundance of commercially available software for fleet management, they often lack the capability to deal properly with sequencing problems and dynamic revision of plans and schedules during process execution. Our approach to achieve better solutions for the waste collection process is to model it as a vehicle routing problem, more specifically as a team orienteering problem where capacity constraints on the vehicles are considered, as well as time windows for the waste collection points and for the vehicles. The final model is called capacitated team orienteering problem with double time windows (CTOPdTW).We developed a genetic algorithm to solve routing problems in waste collection modelled as a CTOPdTW. The results achieved suggest possible reductions of logistic costs in selective waste collection.

Programa de atividade física e saúde - Projeto M&M: análise da intervenção relativamente ao perímetro de cintura e aptidão cardiorrespiratória

Relatório de estágio de mestrado em Ensino de Educação Física nos Ensinos Básico e Secundário

O ensino experimental das ciências: mudança concetual a partir das conceções alternativas dos alunos do 1.º Ciclo do Ensino Básico

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico

HEP-Frame: A software engineered framework to aid the development and efficient multicore execution of scientific code

This work was supported by FCT (Fundação para a Ciência e Tecnologia) within Project Scope (UID/CEC/00319/2013), by LIP (Laboratório de Instrumentação e Física Experimental de Partículas) and by Project Search-ON2 (NORTE-07-0162- FEDER-000086), co-funded by the North Portugal Regional Operational Programme (ON.2 - O Novo Norte), under the National Strategic Reference Framework, through the European Regional Development Fund.

Improving selective collection of urban waste using a business intelligence system

Today recovering urban waste requires effective management services, which usually imply sophisticated monitoring and analysis mechanisms. This is essential for the smooth running of the entire recycling process as well as for planning and control urban waste recovering. In this paper we present a business intelligence system especially designed and im- plemented to support regular decision-making tasks on urban waste management processes. The system provides a set of domain-oriented analytical tools for studying and characterizing poten- tial scenarios of collection processes of urban waste, as well as for supporting waste manage- ment in urban areas, allowing for the organization and optimization of collection services. In or- der to clarify the way the system was developed and the how it operates, particularly in process visualization and data analysis, we also present the organization model of the system, the ser- vices it disposes, and the interface platforms for exploring data.

Transporte ativo entre casa e escola: estudo de uma escola urbana de 2º ciclo

Relatório de atividade profissional de mestrado em Ensino de Educação Física nos Ensinos Básico e Secundário

Temporal analysis of CHAVE collection

Lecture Notes in Computer Science, 9309

Instrumentos de políticas públicas do turismo: uma análise empírica dos municípios portugueses

Tese de Doutoramento em Ciências da Administração

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Ex situ collection of Limonium spp.: cytogenetic and reproductive characterization for the conservation of rare species

Dissertação mestrado em Biologia Molecular, Biotecnologia e Bioempreendedorismo em Plantas

A systematic study of the structural and magnetic properties of Mn-, Co-, and Ni-Doped Colloidal Fe3O4 nanoparticles

A series of colloidal MxFe3-xO4 (M = Mn, Co, Ni; x = 0–1) nanoparticles with diameters ranging from 6.8 to 11.6 nm was synthesized by hydrothermal reaction in aqueous medium at low temperature (200 °C). Energy-dispersive X-ray microa-nalysis and inductively coupled plasma spectrometry confirms that the actual elemental compositions agree well with the nominal ones. The structural properties of obtained nanoparticles were investigated by using powder X-ray diffraction, Raman scattering, Mössbauer spectroscopy, and electron microscopy. The results demonstrate that our synthesis technique leads to the formation of chemically uniform single-phase solid solution nanoparticles with cubic spinel structure, confirming the intrinsic doping. Magnetic studies showed that, in comparison to Fe3O4, the saturation magnetization of MxFe3-xO4 (M = Mn, Ni) decreases with increasing dopant concentration, while Co-doped samples showed similar saturation magnetizations. On other hand, whereas Mn- and Ni-doped nanoparticles exhibits superparamagnetic behavior at room temperature, ferromagnetism emerges for CoxFe3-xO4 nanoparticles, which can be tuned by the level of Co doping.

Data analytics: abordagem para visualização da informação

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação