Experimental research on rubble stone masonry walls

HMC08 - 1st Historical Mortars Conference: Characterization, Diagnosis, Conservation, Repair and Compatibility, LNEC, Lisbon, 24-26 September 2008This paper refers to the results of a research project carried out at Nova University of Lisbon (Pinho [8]), where several experimental models of rubble stone masonry walls were subjected to axial compression and shear-compression tests. The aim of this research project was the experimental evaluation of some structural strengthening solutions for rubble stone masonry buildings. The results of some tests performed to determine physical, chemical and mechanical properties of the constituent materials of the experimental masonry models are also presented. This experimental work was made in cooperation with LNEC, and it was sponsored by some industrial companies

Durability aspects related to rubble stone masonry walls strengthened with reinforced micro-concrete layers

International Seminar on Seismic Risk and Rehabilitation of Stone Masonry Housing, Azores, Portugal, 1998This paper analyses durability aspects related to the use of reinforced micro-concrete as strengthening material of ancient rubble stone masonry walls. The present study is a section of a research project carried out at the New University of Lisbon (Pinho, 2007), to evaluate some structural strengthening solutions for rubble stone masonry buildings. These kind of strengthening solutions, using sprayed micro-concrete layers (shotcrete layers), are very common in Portugal, namely in the rehabilitation of ancient buildings, as may be seen in Azores, after the earthquake of 1998

On requirements engineering for reactive systems: a formal methodology

This paper introduces a rigorous methodology for requirements specification of systems that react to external stimulus and consequently evolve through different operational modes, providing, in each of them, different functionalities. The proposed methodology proceeds in three stages, enriching a simple state- machine with local algebraic specifications. It resorts to an expressive variant of hybrid logic which is latter translated into first-order to allow for ample automatic tool support

Control of the root lesion Pratylenchus penetrans - the effect of nematocidal activity of plant-derived compounds

The root lesion nematode, Pratylenchus penetrans, is one of the most harmful plant parasites, responsible for worldwide productivity losses in a significant number of plant hosts. Generally, chemical control relies on synthetic compounds used through fumigation or direct contact, which offers a systemic protection. These control methods are costly and hazardous to the environment and to humans. Phytochemicals may play an important role in nematode control. The nematicidal activity of eight compounds that occur naturaly in plants, from two classes of compounds, was assessed at 2 mg/mL, for 24 h. Bioassays were performed following the standard direct contact methodology. P. penetrans was remarkably tolerant to the tested compounds, with mortality range between 1.0 and 5.8 %. To the best of our knowledge, the nematicidal activity of 4 phenolic compounds (catechin, caffeic acid, gallic acid and gentisic acid) was evaluated for the first time for P. penetrans

Segmentation of pathological liver tissue with Dilated Fully Convolutional Networks: A Preliminary Study

Early detection of liver cancer, whether from primary occurrence or from metastization is highly important to establish informed treatment decisions. Accurate delineation of the liver tissues of interest facilitates quantitative assessment of the regions of interest, treatment application, and prognosis. Segmentation of the liver in Computer Tomography (CT) images allows the extraction of the three-dimensional (3D) structure of the liver tissues in which the observation of their relative position to one another is particularly important in treatment scenarios of radiation therapy or interventional surgery planning. The adequate receptive field for the segmentation of such a big organ in CT images, from the remaining neighbouring organs was very successfully improved by the use of the state-of-the-art Convolutional Neural Networks (CNN) algorithms, however, certain issues still arise and are highly dependent of pre-or post-processing methods to refine the final segmentations. Here, the effects of Dilated Convolutional Networks is proposed, for the purpose of improving segmentation of liver tissues in CT. The introduction of a dilation module allowed the concatenation of feature maps with a richer contextual information. The hierarchical learning process given by different dilated convolutional layers is analysed quantitatively. Experiments on the MICCAI Lits challenge dataset are described achieving segmentations with a mean Dice coefficients of 95.57% and 59.36% for the liver and liver tumour, using a total number 30 CT test volumes. (c) ENBENG 2019. All Rights Reserved

Robotic implantation of intracerebral electrodes for deep brain stimulation

This dissertation objective is to contribute for the development of a robotic system towards neurosurgery assistance in Deep Brain Stimulation (DBS) stereotactic procedures. Being DBS neurosurgery typically a long, physically and cognitively demanding procedure; the introduction of a robotic assistant to hold, manipulate and position instrumentation would improve the medical team working conditions and lead to better surgery outcomes. Upon understanding how could the robot be used and what robotic systems were adequate to the task, we implemented a simulation environment to emulate several industrial robot manipulators and the operating room. It was also developed each robot geometric and differential kinematic equations, and control algorithms specifically oriented for DBS neurosurgery assistance. Taking into account the operating room arrangement, the robot characteristics and task requirements, we selected the most apt industrial robotic manipulator and further elaborated on its placement and orientation to achieve utmost performance.This work has been partially financed by projects FP7 Marie Curie ITN - NETT (project no289146), FCT FCOMP-01-0124-FEDER-022674, Pest-C/MAT-UI0013/2011 (FCT grant ref. UMINHO/BIC/8/2012) and FCT PhD grant (ref. SFRH/BD/86499/2012)

Análise in vitro da distribuição de tensões em implantes angulados de diferentes comprimentos

: Neste trabalho apresenta-se um estudo realizado para avaliar computacionalmente ouso de implantes curtos em reabilitação mandibular total com base no Método dos ElementosFinitos. Em particular, verifica-se como o comprimento desses implantes influencia adistribuição de tensões durante a aplicação de cargas mastigatórias em reabilitaçõesmandibulares de acordo com o conceito All-on-4®

Enhanced performance of cobalt ferrite encapsulated in graphitic shell by means of AC magnetically activated catalytic wet peroxide oxidation of 4-nitrophenol

Here we report preliminary catalytic wet peroxide oxidation (CWPO) experiments performed in the presence of an alternating current (AC) magnetic field. One ferromagnetic graphitic nanocomposite - composed by a cobalt ferrite core and a graphitic shell (CoFe2O4/MGNC), was employed in the process, here named magnetically activated catalytic wet peroxide oxidation (MA-CWPO). An aqueous solution containing 5.0 g L-1 of 4-nitrophenol (4-NP) to simulate a high strength polluted stream was used as model system. The experiments were performed at room temperature and atmospheric pressure, with stoichiometric amount of hydrogen peroxide (H2O2), pH = 3 and CoFe2O4/MGNC catalyst load = 5.0 g L-1 (corresponding to a 4-NP/CoFe2O4 mass ratio of 6.9, as CoFe2O4 accounts for 14.4 wt% of CoFe2O4/MGNC). It was shown that the performance of CWPO is enhanced upon application of an AC magnetic field (frequency of 533.9 kHz and magnitude of 240 G). As a result, high 4-NP mineralization was obtained by MA-CWPO (as reflected by a total organic carbon abatement of 79% after 4 h of reaction, instead of 39% in the absence of a magnetic field). This positive effect was ascribed to the localised increase of CoFe2O4/MGNC surface temperature resulting from heat release upon exposure of the nanoparticulated catalyst to an AC magnetic field, which accelerates the catalytic decomposition of H2O2 via hydroxyl radicals (HO center dot) formation

Extraction, selection and comparison of features for an effective automated computer-aided diagnosis of Parkinson's disease based on [123I]FP-CIT SPECT images

Purpose This work aimed to assess the potential of a set of features extracted from [I-123] FP-CIT SPECT brain images to be used in the computer-aided "in vivo" confirmation of dopaminergic degeneration and therefore to assist clinical decision to diagnose Parkinson's disease.Methods Seven features were computed from each brain hemisphere: five standard features related to uptake ratios on the striatum and two features related to the estimated volume and length of the striatal region with normal uptake. The features were tested on a dataset of 652 [I-123] FP-CIT SPECT brain images from the Parkinson's Progression Markers Initiative. The discrimination capacities of each feature individually and groups of features were assessed using three different machine learning techniques: support vector machines (SVM), k-nearest neighbors and logistic regression.Results Cross-validation results based on SVM have shown that, individually, the features that generated the highest accuracies were the length of the striatal region (96.5%), the putaminal binding potential (95.4%) and the striatal binding potential (93.9%) with no statistically significant differences among them. The highest classification accuracy was obtained using all features simultaneously (accuracy 97.9%, sensitivity 98% and specificity 97.6%). Generally, slightly better results were obtained using the SVM with no statistically significant difference to the other classifiers for most of the features.Conclusions The length of the striatal region uptake is clinically useful and highly valuable to confirm dopaminergic degeneration "in vivo" as an aid to the diagnosis of Parkinson's disease. It compares fairly well to the standard uptake ratio-based features, reaching, at least, similar accuracies and is easier to obtain automatically. Thus, we propose its day to day clinical use, jointly with the uptake ratio-based features, in the computer-aided diagnosis of dopaminergic degeneration in Parkinson's disease