Predicting type of delivery by identification of obstetric risk factors through data mining

In Maternity Care, a quick decision has to be made about the most suitable delivery type for the current patient. Guidelines are followed by physicians to support that decision; however, those practice recommendations are limited and underused. In the last years, caesarean delivery has been pursued in over 28% of pregnancies, and other operative techniques regarding specific problems have also been excessively employed. This study identifies obstetric and pregnancy factors that can be used to predict the most appropriate delivery technique, through the induction of data mining models using real data gathered in the perinatal and maternal care unit of Centro Hospitalar of Oporto (CHP). Predicting the type of birth envisions high-quality services, increased safety and effectiveness of specific practices to help guide maternity care decisions and facilitate optimal outcomes in mother and child. In this work was possible to acquire good results, achieving sensitivity and specificity values of 90.11% and 80.05%, respectively, providing the CHP with a model capable of correctly identify caesarean sections and vaginal deliveries.

Impact performance prediction of injection-molded talc-filled polypropylene through thermomechanical environment assessment

Due to the fact that different injection molding conditions tailor the mechanical response of the thermoplastic material, such effect must be considered earlier in the product development process. The existing approaches implemented in different commercial software solutions are very limited in their capabilities to estimate the influence of processing conditions on the mechanical properties. Thus, the accuracy of predictive simulations could be improved. In this study, we demonstrate how to establish straightforward processing-impact property relationships of talc-filled injection-molded polypropylene disc-shaped parts by assessing the thermomechanical environment (TME). To investigate the relationship between impact properties and the key operative variables (flow rate, melt and mold temperature, and holding pressure), the design of experiments approach was applied to systematically vary the TME of molded samples. The TME is characterized on computer flow simulation outputsanddefined bytwo thermomechanical indices (TMI): the cooling index (CI; associated to the core features) and the thermo-stress index (TSI; related to the skin features). The TMI methodology coupled to an integrated simulation program has been developed as a tool to predict the impact response. The dynamic impact properties (peak force, peak energy, and puncture energy) were evaluated using instrumented falling weight impact tests and were all found to be similarly affected by the imposed TME. The most important molding parameters affecting the impact properties were found to be the processing temperatures (melt andmold). CI revealed greater importance for the impact response than TSI. The developed integrative tool provided truthful predictions for the envisaged impact properties.

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Promoting independent living and recreation in life through ambient assisted living technology

The increase in life expectancy with a decrease in birth rates is contributing to the ageing of the European population. This phenomenon, coupled with greater awareness of the quality of life, the need to have cost-efficient assistive care, the intention of people to live independently in their homes, and the technological developments in recent decades, have contributed to the emergence of the concept of ambient assisted living (AAL). AAL solutions aim to provide healthy and safe ageing to users through promoting independence in performing daily activities and interacting with technology, taking into consideration the deterioration of the users’ capabilities and the reduced costs of the solutions. In this chapter, AAL developments of monitoring activities of daily living (ADLs) and participation in a virtual community with the selected stakeholders are introduced, their roadmap with the expected technological developments are described, and the expected impact of these solutions on the end users of the developed solutions are discussed. This enables a real user guidance structure that represents the different needs and limitations of each user, presenting a highly structured project based on personas and possible solutions for them. The AAL4ALL Ambient Assisted Living for All (ALL4ALL) project is considered here as a case study to analyze and illustrate the ALL concepts discussed in this chapter.

Spatial-temporal modellization of the NO2 concentration data through geostatistical tools

The nitrogen dioxide is a primary pollutant, regarded for the estimation of the air quality index, whose excessive presence may cause significant environmental and health problems. In the current work, we suggest characterizing the evolution of NO2 levels, by using geostatisti- cal approaches that deal with both the space and time coordinates. To develop our proposal, a first exploratory analysis was carried out on daily values of the target variable, daily measured in Portugal from 2004 to 2012, which led to identify three influential covariates (type of site, environment and month of measurement). In a second step, appropriate geostatistical tools were applied to model the trend and the space-time variability, thus enabling us to use the kriging techniques for prediction, without requiring data from a dense monitoring network. This method- ology has valuable applications, as it can provide accurate assessment of the nitrogen dioxide concentrations at sites where either data have been lost or there is no monitoring station nearby.

On simple bounds for eigenvalues of symmetric tridiagonal matrices

How much can be said about the location of the eigenvalues of a symmetric tridiagonal matrix just by looking at its diagonal entries? We use classical results on the eigenvalues of symmetric matrices to show that the diagonal entries are bounds for some of the eigenvalues regardless of the size of the off-diagonal entries. Numerical examples are given to illustrate that our arithmetic-free technique delivers useful information on the location of the eigenvalues.

Comunicação Android com câmaras ONVIF e gestão de Perfis de Media

Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática

Efeito da dissipação térmica nas juntas de soldagem de componentes through hole

Dissertação de mestrado integrado em Engenharia de Materiais

Synthesis of iminosugars through diastereo/enantioselective diels-alder cycloaddition

Tese de Doutoramento em Ciências (Especialidade em Química)

A network approach to brain aging through multimodal neuroimaging

Tese de Doutoramento em Ciências da Saúde.

Cathepsin D protects colorectal cancer cells from acetate-induced apoptosis through autophagy-independent degradation of damaged mitochondria

Acetate is a short-chain fatty acid secreted by Propionibacteria from the human intestine, known to induce mitochondrial apoptotic death in colorectal cancer (CRC) cells. We previously established that acetate also induces lysosome membrane permeabilization in CRC cells, associated with release of the lysosomal protease cathepsin D (CatD), which has a well-established role in the mitochondrial apoptotic cascade. Unexpectedly, we showed that CatD has an antiapoptotic role in this process, as pepstatin A (a CatD inhibitor) increased acetate-induced apoptosis. These results mimicked our previous data in the yeast system showing that acetic acid activates a mitochondria-dependent apoptosis process associated with vacuolar membrane permeabilization and release of the vacuolar protease Pep4p, ortholog of mammalian CatD. Indeed, this protease was required for cell survival in a manner dependent on its catalytic activity and for efficient mitochondrial degradation independently of autophagy. In this study, we therefore assessed the role of CatD in acetate-induced mitochondrial alterations. We found that, similar to acetic acid in yeast, acetate-induced apoptosis is not associated with autophagy induction in CRC cells. Moreover, inhibition of CatD with small interfering RNA or pepstatin A enhanced apoptosis associated with higher mitochondrial dysfunction and increased mitochondrial mass. This effect seems to be specific, as inhibition of CatB and CatL with E-64d had no effect, nor were these proteases significantly released to the cytosol during acetate-induced apoptosis. Using yeast cells, we further show that the role of Pep4p in mitochondrial degradation depends on its protease activity and is complemented by CatD, indicating that this mechanism is conserved. In summary, the clues provided by the yeast model unveiled a novel CatD function in the degradation of damaged mitochondria when autophagy is impaired, which protects CRC cells from acetate-induced apoptosis. CatD inhibitors could therefore enhance acetate-mediated cancer cell death, presenting a novel strategy for prevention or therapy of CRC.

SMYD3 contributes to a more aggressive phenotype of prostate cancer and targets Cyclin D2 through H4K20me3

Prostate cancer (PCa) is one of the most incident cancers worldwide but clinical and pathological parameters have limited ability to discriminate between clinically significant and indolent PCa. Altered expression of histone methyltransferases and histone methylation patterns are involved in prostate carcinogenesis. SMYD3 transcript levels have prognostic value and discriminate among PCa with different clinical aggressiveness, so we decided to investigate its putative oncogenic role on PCa.We silenced SMYD3 and assess its impact through in vitro (cell viability, cell cycle, apoptosis, migration, invasion assays) and in vivo (tumor formation, angiogenesis). We evaluated SET domain's impact in PCa cells' phenotype. Histone marks deposition on SMYD3 putative target genes was assessed by ChIP analysis.Knockdown of SMYD3 attenuated malignant phenotype of LNCaP and PC3 cell lines. Deletions affecting the SET domain showed phenotypic impact similar to SMYD3 silencing, suggesting that tumorigenic effect is mediated through its histone methyltransferase activity. Moreover, CCND2 was identified as a putative target gene for SMYD3 transcriptional regulation, through trimethylation of H4K20.Our results support a proto-oncogenic role for SMYD3 in prostate carcinogenesis, mainly due to its methyltransferase enzymatic activity. Thus, SMYD3 overexpression is a potential biomarker for clinically aggressive disease and an attractive therapeutic target in PCa.

Dynamic wet etching of silicon through isopropanol alcohol evaporation

In this paper, Isopropanol (IPA) availability during the anisotropic etching of silicon in Potassium Hydroxide (KOH) solutions was investigated. Squares of 8 to 40 m were patterned to (100) oriented silicon wafers through DWL (Direct Writing Laser) photolithography. The wet etching process was performed inside an open HDPE (High Density Polyethylene) flask with ultrasonic agitation. IPA volume and evaporation was studied in a dynamic etching process, and subsequent influence on the silicon etching was inspected. For the tested conditions, evaporation rates for water vapor and IPA were determined as approximately 0.0417 mL/min and 0.175 mL/min, respectively. Results demonstrate that IPA availability, and not concentration, plays an important role in the definition of the final structure. Transversal SEM (Scanning Electron Microscopy) analysis demonstrates a correlation between microloading effects (as a consequence of structure spacing) and the angle formed towards the (100) plane.

Resilience of concrete structures in the marine environment through microstructural innovation

Dissertação de mestrado integrado em Engenharia Civil

Design of bio-based supramolecular structures through self-assembly of α-lactalbumin and lysozyme

Bovine α-lactalbumin (α-La) and lysozyme (Lys), two globular proteins with highly homologous tertiary structures and opposite isoelectric points, were used to produce bio-based supramolecular structures under various pH values (3, 7 and 11), temperatures (25, 50 and 75 °C) and times (15, 25 and 35 min) of heating. Isothermal titration calorimetry experiments showed protein interactions and demonstrated that structures were obtained from the mixture of α-La/Lys in molar ratio of 0.546. Structures were characterized in terms of morphology by transmission electron microscopy (TEM) and dynamic light scattering (DLS), conformational structure by circular dichroism and intrinsic fluorescence spectroscopy and stability by DLS. Results have shown that protein conformational structure and intermolecular interactions are controlled by the physicochemical conditions applied. The increase of heating temperature led to a significant decrease in size and polydispersity (PDI) of α-La–Lys supramolecular structures, while the increase of heating time, particularly at temperatures above 50 °C, promoted a significant increase in size and PDI. At pH 7 supramolecular structures were obtained at microscale – confirmed by optical microscopy – displaying also a high PDI (i.e. > 0.4). The minimum size and PDI (61 ± 2.3 nm and 0.14 ± 0.03, respectively) were produced at pH 11 for a heating treatment of 75 °C for 15 min, thus suggesting that these conditions could be considered as critical for supramolecular structure formation. Its size and morphology were confirmed by TEM showing a well-defined spherical form. Structures at these conditions showed to be stable at least for 30 or 90 days, when stored at 25 or 4 °C, respectively. Hence, α-La–Lys supramolecular structures showed properties that indicate that they are a promising delivery system for food and pharmaceutical applications.