11 resultados para integrated project delivery
em Universidade do Minho
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Dissertação de mestrado integrado em Civil Engineering
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Dissertação de mestrado em Construção e Reabilitação Sustentáveis
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In this paper, we present an integrated system for real-time automatic detection of human actions from video. The proposed approach uses the boundary of humans as the main feature for recognizing actions. Background subtraction is performed using Gaussian mixture model. Then, features are extracted from silhouettes and Vector Quantization is used to map features into symbols (bag of words approach). Finally, actions are detected using the Hidden Markov Model. The proposed system was validated using a newly collected real- world dataset. The obtained results show that the system is capable of achieving robust human detection, in both indoor and outdoor environments. Moreover, promising classification results were achieved when detecting two basic human actions: walking and sitting.
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This article compiles the main topics addressed by management systems (MSs) literature concerningMSs integration by performing a systematic literature review. In this paper, it is intended to present themain limitations of non-integratedmanagement systems (IMSs), the main motivations driving an IMS implementation, the major resistances faced, the most common resultant benefits, the suitable guidelines and standards and the critical success factors. In addition, this paper addresses the issues concerning integration strategies and models, the integration levels or degrees achieved by an IMS and the audit function in an integrated context. The motivations that drive companies to integrate their management subsystems, the obstacles faced and the benefits collected may have internal or external origins. The publishing of standards guiding companies on how to integrate their management subsystems has been done mainly at a national level. There are several models that could be used in order to support companies in their management subsystems integration processes, and a sequential or an all-in strategy may be adopted. Four audit typologies can be distinguished, and the adoption of any of these typologies should consider resource availability and audit team know-how, among other features.
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Maturity models are adopted to minimise our complexity perception over a truly complex phenomenon. In this sense, maturity models are tools that enable the assessment of the most relevant variables that impact on the outputs of a specific system. Ideally a maturity model should provide information concerning the qualitative and quantitative relationships between variables and how they affect the latent variable, that is, the maturity level. Management systems (MSs) are implemented worldwide and by an increasing number of companies. Integrated management systems (IMSs) consider the implementation of one or several MSs usually coexisting with the quality management subsystem (QMS). It is intended in this chapter to report a model based on two components that enables the assessment of the IMS maturity, considering the key process agents (KPAs) identified through a systematic literature review and the results collected from two surveys.
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Efficient liposome disruption inside the cells is a key for success with any type of drug delivery system. The efficacy of drug delivery is currently evaluated by direct visualization of labeled liposomes internalized by cells, not addressing objectively the release and distribution of the drug. Here, we propose a novel method to easily assess liposome disruption and drug release into the cytoplasm. We propose the encapsulation of the cationic dye Hoechst 34,580 to detect an increase in blue fluorescence due to its specific binding to negatively charged DNA. For that, the dye needs to be released inside the cell and translocated to the nucleus. The present approach correlates the intensity of detected fluorescent dye with liposome disruption and consequently assesses drug delivery within the cells.
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Poly(dimethylsiloxane) (PDMS) is an organosilicon polymer widely used in the fabrication of microfluidic systems to integrate biochips. In this study, we propose the use of an adapted PDMS mould for the creation of a miniaturized, reusable, reference electrode for in-chip electrochemical measurements. Through its integrated microfluidic system it is possible to replenish internal buffer solutions, unclog critical junctions and treat the electrode’s surface, assuring a long term reuse of the same device. Planar Ag/AgCl reference electrodes were microfabricated over a passivated p-type Silicon Wafer. The PDMS mould, containing an integrated microfluidic system, was fabricated based on patterned SU-8 mould, which includes a lateral horizontal inlet access point. Surface oxidation was used for irreversible permanent bondage between flat surfaces. The final result was planar Ag/AgCl reference electrode with integrated microfluidic that allows for electrochemical analysis in biochips
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The potential of salicylic acid (SA) encapsulated in porous materials as drug delivery carriers for cancer treatment was studied. Different porous structures, the microporous zeolite NaY, and the mesoporous SBA-15 and MCM-41 were used as hosts for the anti-inflammatory drug. Characterization with different techniques (FTIR, UV/vis, TGA, 1H NMR, and 13C CPMAS NMR) demonstrated the successful loading of SA into the porous hosts. The mesoporous structures showed to be very efficient to encapsulate the SA molecule. The obtained drug delivery systems (DDS) accommodated 0.74 mmol (341 mg/gZEO) in NaY and 1.07 mmol (493 mg/gZEO) to 1.23 mmol (566 mg/gZEO) for SBA-15 and MCM-41, respectively. Interactions between SA molecules and pore structures were identified. A fast and unrestricted liberation of SA at 10 min of the dissolution assay was achieved with 29.3, 46.6, and 50.1 µg/mL of SA from NaY, SBA-15, and MCM-41, respectively, in the in vitro drug release studies (PBS buffer pH 7.4, 37 °C). Kinetic modeling was used to determine the release patterns of the DDS. The porous structures and DDS were evaluated on Hs578T and MDA-MB-468 breast cancer cell lines viability. The porous structures are nontoxic to cancer cells. Cell viability reduction was only observed after the release of SA from MCM- 41 followed by SBA-15 in both breast cancer cell lines.
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Oceans are a vast source of natural substances. In them, we find various compounds with wide biotechnological and biomedical applicabilities. The exploitation of the sea as a renewable source of biocompounds can have a positive impact on the development of new systems and devices for biomedical applications. Marine polysaccharides are among the most abundant materials in the seas, which contributes to a decrease of the extraction costs, besides their solubility behavior in aqueous solvents and extraction media, and their interaction with other biocompounds. Polysaccharides such as alginate, carrageenan and fucoidan can be extracted from algae, whereas chitosan and hyaluronan can be obtained from animal sources. Most marine polysaccharides have important biological properties such as biocompatibility, biodegradability, and anti-inflammatory activity, as well as adhesive and antimicrobial actions. Moreover, they can be modified in order to allow processing them into various shapes and sizes and may exhibit response dependence to external stimuli, such as pH and temperature. Due to these properties, these biomaterials have been studied as raw material for the construction of carrier devices for drugs, including particles, capsules and hydrogels. The devices are designed to achieve a controlled release of therapeutic agents in an attempt to fight against serious diseases, and to be used in advanced therapies, such as gene delivery or regenerative medicine.
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The efficient utilization of lignocellulosic biomass and the reduction of production cost are mandatory to attain a cost-effective lignocellulose-to-ethanol process. The selection of suitable pretreatment that allows an effective fractionation of biomass and the use of pretreated material at high-solid loadings on saccharification and fermentation (SSF) processes are considered promising strategies for that purpose. Eucalyptus globulus wood was fractionated by organosolv process at 200 C for 69 min using 56% of glycerol-water. A 99% of cellulose remained in pretreated biomass and 65% of lignin was solubilized. Precipitated lignin was characterized for chemical composition and thermal behavior, showing similar features to commercial lignin. In order to produce lignocellulosic ethanol at high-gravity, a full factory design was carried to assess the liquid to solid ratio (3e9 g/g) and enzyme to solid ratio (8e16 FPU/g) on SSF of delignified Eucalyptus. High ethanol concentration (94 g/L) corresponding to 77% of conversion at 16FPU/g and LSR ¼ 3 g/g using an industrial and thermotolerant Saccharomyces cerevisiae strain was successfully produced from pretreated biomass. Process integration of a suitable pretreatment, which allows for whole biomass valorization, with intensified saccharification-fermentation stages was shown to be feasible strategy for the co-production of high ethanol titers, oligosaccharides and lignin paving the way for cost-effective Eucalyptus biorefinery.
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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.