Estimativa dos parâmetros de compactação de solos usando técnicas de data mining

Dissertação de mestrado integrado em Engenharia Civil

An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Thermal–mechanical behaviour of chitosan–cellulose derivative thermoreversible hydrogel films

CH, Chitosan; HPMC, (Hydroxypropyl)methyl cellulose; FT, Freeze-thaw; SC, Solvent casting; CH:HPMC (X:Y), pH Z, FT/SC, Chitosan and (hydroxypropyl)methyl cellulose hydrogel, at X and Y proportion (0-100), at Z pH (3.0-4.0) and prepared by freeze-thaw or solvent casting techniques; DSC, Differential scanning calorimetry; MDSC, Temperature modulated Differential scanning calorimetry; Tg, glass transition temperature; ΔH, enthalpy change; TGA, Thermogravimetric Analysis; TG, Thermogravimetry; DTG, Derivative or Differential thermogravimetry; σ, Tensile strength; ε, elongation at break; DMA, Dynamic mechanical analysis; X-Ray, X-radiation, FTIR-ATR, Attenuated total reflectance Fourier transform infrared spectroscopy; SEM, Scanning electron microscopy.

Erratum to: Thermal–mechanical behaviour of chitosan–cellulose derivative thermoreversible hydrogel films

CH, Chitosan; HPMC, (Hydroxypropyl)methyl cellulose; FT, Freeze-thaw; SC, Solvent casting; CH:HPMC (X:Y), pH Z, FT/SC, Chitosan and (hydroxypropyl)methyl cellulose hydrogel, at X and Y proportion (0-100), at Z pH (3.0-4.0) and prepared by freeze-thaw or solvent casting techniques; DSC, Differential scanning calorimetry; MDSC, Temperature modulated Differential scanning calorimetry; Tg, glass transition temperature; ΔH, enthalpy change; TGA, Thermogravimetric Analysis; TG, Thermogravimetry; DTG, Derivative or Differential thermogravimetry; σ, Tensile strength; ε, elongation at break; DMA, Dynamic mechanical analysis; X-Ray, X-radiation, FTIR-ATR, Attenuated total reflectance Fourier transform infrared spectroscopy; SEM, Scanning electron microscopy.

Bioactive ceramics for tissue engineering and regenerative medicine derived from marine sponges

Publicado em "Journal of tissue engineering and regenerative medicine". Vol. 8, suppl. s1 (2014)

Development of polymeric nanoparticles containing neuroprotective compounds of Hypericum perforatum

Tese de Doutoramento em Biologia das Plantas - MAP BIOPLANT

Adhesive bioactive coatings inspired by sea life

Inspired by nature, in particular by the marine mussels adhesive proteins (MAPs) and by the tough brick-and-mortar nacre-like structure, novel multilayered films are prepared in the present work. Organic-inorganic multilayered films, with an architecture similar to nacre based on bioactive glass nanoparticles (BG), chitosan and hyaluronic acid modified with catechol groups, which are the main responsible for the outstanding adhesion in MAPs, are developed for the first time. The biomimetic conjugate is prepared by carbodiimide chemistry and analyzed by ultraviolet-visible spectrophotometry. The build-up of the multilayered films is monitored with a quartz crystal microbalance with dissipation monitoring and their topography is characterized by atomic force microscopy. The mechanical properties reveal that the films containing catechol groups and BG present an enhanced adhesion. Moreover, the bioactivity of the films upon immersion in a simulated body fluid solution for 7 days is evaluated by scanning electron microscopy coupled with energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy and X-ray diffraction. It was found that the constructed films promote the formation of bone-like apatite in vitro. Such multifunctional mussel inspired LbL films, which combine enhanced adhesion and bioactivity, could be potentially used as coatings of a variety of implants for orthopedic applications.

Effects of fermentation residues on the melt processability and thermomechanical degradation of PHBV produced from cheese whey using mixed microbial cultures

"Available online 28 March 2016"

Development of active bio-based multilayer systems: encapsulation of cinnamaldehyde and their physicochemical characterization

[Excerpt] In this work, different multilayer structures, using a polyhydroxybutyrate-co-valerate film with a valerate content of 8% (PHBV8) as support, were developed aiming the development of active bio-based multilayer systems. An interlayer based on zein nanofibers with and without cinnamaldehyde were electrospun in the PHBV8 film and three multilayer systems were developed: 1) without an outer layer; 2) using a PHBV8 film as outer layer; and 3) using an alginate-based film as outer layer. Their physico-chemical properties were evaluated through: water vapour and oxygen permeabilities and colour measurements, Fourier Transform Infrared Spectroscopy (FTIR) and thermal analyses. Results showed that the presence of different outer layers affected the water vapour permeability and transparency of the multilayer films. (...)