Estratégias de raciocínio clínico dos enfermeiros que cuidam de clientes em situação crítica: revisão sistemática da literatura

Identificar estratégias de raciocínio clínico dos enfermeiros que cuidam de clientes, em situação crítica. Foi realizada uma revisão sistemática da literatura com recurso ao método PI[C]O na EBSCO (CINAHL (Plus with Full Text), MEDLINE (Plus with Full Text)) com limitador temporal entre 2009-2015, dos quais foram selecionados 8 artigos. As estratégias de raciocínio clínico de enfermagem que emergiram foram: a relação de confiança com o cliente e envolvimento da família, aplicação de competências de negociação e compromisso, de competências crítico-reflexivas, a intuição, o reconhecimento de situações similares e teste de hipóteses. E, como critérios de raciocínio clínico, o enfermeiro avalia o risco-benefício para o cliente, avalia as necessidades organizacionais e pesquisa informação em fontes complementares(11). Esta revisão permitiu conhecer algumas estratégias e critérios de raciocínio clínico do enfermeiro que cuida de clientes em situação crítica. No entanto, são necessários mais estudos para aprofundar conhecimento sobre o processo de raciocínio clínico que promove resultados positivos para o cliente decorrentes da intervenção autónoma e capacidade de decisão da enfermagem. Descritores: Raciocínio Clínico; tomada de decisão; cuidados de enfermagem

Stability and decolourization ability of trametes villosa laccase in liquid ultrasonic fields

We report in this study that the sonication of laccase from Trametes villosa and bovine serum albumin promotes the formation of protein aggregates with high molecular weight. The formation of aggregates leads to the deactivation of the enzyme, fact that was confirmed by the analysis of the enzyme stability (half-life time) upon ultrasound treatment. This inactivation was mainly caused by the radicals formed by the cavitation phenomenon. It was verified that the addition of polyvinyl alcohol to laccase had a protecting effect against enzyme inactivation. The performance of laccase in the decolourization of indigo carmine was studied. It was observed that the best results were attained when the dye solution was treated with ultrasound and enzyme stabilized with polyvinyl alcohol, where more than 65% of decolourization was achieved. This value is remarkably higher than that attained for the enzyme alone, which was only able to decolourize 20% of the dye solution within 1 h of treatment. These results have important implications for the exploitation of sonication in textile industry, where the pollution caused by the release of dyes into effluents is one of the major concerns.Fundação para a Ciência e a Tecnologia (FCT) - SFRH/BD/8651/2002União Europeia - Projecto ULTRATEC (NMP2- CT-2003-505892)

Agrio et Emulsio – development of fruity mustard creams

Agrio et Emulsio project (POCI-01-0145-FEDER-023583) presents an proposal in the areas of vinegar products and food emulsions. Combining technical features with mediterranean traditions and Nouvelle Cuisine, two prototypes of fruity mustards are undergoing final development, valuing regional raw materials and profiling into the gourmet/vegan/veggie markets. Mustard creams are oil-in-water emulsions but its practice is linked to vinegar traditions since the thirteenth century, in France, with the foundation of the first confraternity of Maîtres Vinaigrier-Moutardier. Thus, by applying the ancestral practice, mustard (seeds, fragments, powder) was first submitted to maturation studies, varying the type of vinegar and the time of immersion/contact. Maturation reached equilibrium on the 16th day, but pH evolution shows a practically stationary state from the 7th. Best results were obtained with seeds and powdered mustards in red wine vinegar, 4 %(m/v) acidity. The assays were carried out at room temperature using Sinapis Alba (Linnaeus) mustard species. Prototyping articulated technical, analytical (physicochemical, rheological, microbiological) and sensory tests. Each final prototype has a distinct profile of ingredients, mustard, fruits (raspberry and beet or blueberry), olive oil, water, salt, sugar, honey and spices. Both creams retain the sui generis taste of mustard tinted with the fruit flavour plus an innovative pink colour.info:eu-repo/semantics/publishedVersio

An EAI based integration solution for science and research outcomes information management

Open Access articleIn this paper we present an Enterprise Application Integration (EAI) based proposal for research outcomes information management. The proposal is contextualized in terms of national and international science and research outcomes information management, corresponding supporting information systems and ecosystems. Information systems interoperability problems, approaches, technologies and tools are presented and applied to the research outcomes information management case. A business and technological perspective is provided, including the conceptual analysis and modelling, an integration solution based in a Domain-Specific Language (DSL) and the orchestration engine to execute the proposed solution. For illustrative purposes, the role and information system needs of a research unit is assumed as the representative case

Multiobjective optimization of classifiers by means of 3-D convex Hull based evolutionary algorithms

The receiver operating characteristic (ROC) and detection error tradeoff (DET) curves are frequently used in the machine learning community to analyze the performance of binary classifiers. Recently, the convex-hull-based multiobjective genetic programming algorithm was proposed and successfully applied to maximize the convex hull area for binary classification problems by minimizing false positive rate and maximizing true positive rate at the same time using indicator-based evolutionary algorithms. The area under the ROC curve was used for the performance assessment and to guide the search. Here we extend this research and propose two major advancements: Firstly we formulate the algorithm in detection error tradeoff space, minimizing false positives and false negatives, with the advantage that misclassification cost tradeoff can be assessed directly. Secondly, we add complexity as an objective function, which gives rise to a 3D objective space (as opposed to a 2D previous ROC space). A domain specific performance indicator for 3D Pareto front approximations, the volume above DET surface, is introduced, and used to guide the indicator -based evolutionary algorithm to find optimal approximation sets. We assess the performance of the new algorithm on designed theoretical problems with different geometries of Pareto fronts and DET surfaces, and two application-oriented benchmarks: (1) Designing spam filters with low numbers of false rejects, false accepts, and low computational cost using rule ensembles, and (2) finding sparse neural networks for binary classification of test data from the UCI machine learning benchmark. The results show a high performance of the new algorithm as compared to conventional methods for multicriteria optimization.info:eu-repo/semantics/submittedVersio

Large ferro–pyro–phototronic effect in 0.5Ba(Zr0.2Ti0.8)O3–0.5(Ba0.7Ca0.3)TiO3 thin films integrated on silicon for photodetection

Coupling together the ferroelectric, pyroelectric, and photovoltaic characteristics within a single material is a novel way to improve the performance of photodetectors. In this work, we take advantage of the triple multifunctionality shown by 0.5Ba(Zr0.2Ti0.8)O3–0.5(Ba0.7Ca0.3)TiO3 (BCZT), as demonstrated in an Al/Si/SiOx/BCZT/ITO thin-film device. The Si/SiOx acts as an n-type layer to form a metal–ferroelectric–insulator–semiconductor heterostructure with the BCZT, and with Al and ITO as electrodes. The photo-response of the device, with excitation from a violet laser (405 nm wavelength), is carefully investigated, and it is shown that the photodetector performance is invariant with the chopper frequency owing to the pyro-phototronic effect, which corresponds to the coupling together of the pyroelectric and photovoltaic responses. However, the photodetector performance was significantly better than that of the devices operating based only on the pyro-phototronic effect by a factor of 4, due to the presence of ferroelectricity in the system. Thus, after a poling voltage of −15 V, for a laser power density of 230 mW/cm2 and at a chopper frequency of 400 Hz, optimized responsivity, detectivity, and sensitivity values of 13.1 mA/W, 1.7 × 1010 Jones, and 26.9, respectively, are achieved. Furthermore, ultrafast rise and fall times of 2.4 and 1.5 µs, respectively, are obtained, which are 35,000 and 36,000 times faster rise and fall responses, respectively, than previous reports of devices with the ferro–pyro–phototronic effect. This is understood based on the much faster ferroelectric switching in ferroelectric thin films owing to the predominant 180° domains in a single direction out of plane.This work was supported by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Funding Contracts UIDB/04650/2020. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 958174 (M-ERA-NET3/0003/2021—NanOx4EStor). The authors would also like to thank engineer José Santos for technical support at the Thin Film Laboratory. J. L. M.-D. and R. L. Z. H. are grateful for EPSRC CAM-IES grant EP/P007767/. R. L. Z. H. also acknowledges support from the Royal Academy of Engineering under the Research Fellowships scheme (No.: RF\201718\1701). J. L. M.-D. acknowledges support from the Royal Academy of Engineering Chair in Emerging Technologies scheme (No.: CIET1819_24) and the ERC grant EROS, EU-H2020-ERC-ADG # 882929

A spam filtering mult-iobjective optimization study covering parsimony maximization and three-way classification

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Classifier performance optimization in machine learning can be stated as a multi-objective optimization problem. In this context, recent works have shown the utility of simple evolutionary multi-objective algorithms (NSGA-II, SPEA2) to conveniently optimize the global performance of different anti-spam filters. The present work extends existing contributions in the spam filtering domain by using three novel indicator-based (SMS-EMOA, CH-EMOA) and decomposition-based (MOEA/D) evolutionary multi-objective algorithms. The proposed approaches are used to optimize the performance of a heterogeneous ensemble of classifiers into two different but complementary scenarios: parsimony maximization and e-mail classification under low confidence level. Experimental results using a publicly available standard corpus allowed us to identify interesting conclusions regarding both the utility of rule-based classification filters and the appropriateness of a three-way classification system in the spam filtering domain

Assessment of pollution risk ascribed to Santa Margarida Military Camp activities (Portugal)

Santa Margarida Military Camp (S.M.M.C.) is the only one Portuguese military training area, including firing ranges for tactical military manoeuvres of mechanised divisions. For this reason, various negative effects on the environment were expected due to the military activities, as the Military Camp’s area is classified as a high vulnerability area to pollution of its multilayer porous aquifers. The aim of this study was to identify and characterise local/regional geochemical impacts caused by the continuing military training activities performed at S.M.M.C. in the course of 52 years. An overview of the geochemical research issues as a basis for risk assessment is presented. A special attention has been put on the quality of local and regional surface waters, shallow groundwaters and groundwaters. Local soils and sediments as well as fragments of shells and bullets were sampled and analysed. The results so far obtained, indicated that none pollution effects were a consequence of the military training activities. Till now, the geochemical signatures such as, high levels of K, Cl and NO3 in waters, detected in particular sites, should be faced as tracers of diffuse pollution ascribed to urban waste disposal and cattle breading

Improving the drug discovery process by using multiple classifier systems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Machine learning methods have become an indispensable tool for utilizing large knowledge and data repositories in science and technology. In the context of the pharmaceutical domain, the amount of acquired knowledge about the design and synthesis of pharmaceutical agents and bioactive molecules (drugs) is enormous. The primary challenge for automatically discovering new drugs from molecular screening information is related to the high dimensionality of datasets, where a wide range of features is included for each candidate drug. Thus, the implementation of improved techniques to ensure an adequate manipulation and interpretation of data becomes mandatory. To mitigate this problem, our tool (called D2-MCS) can split homogeneously the dataset into several groups (the subset of features) and subsequently, determine the most suitable classifier for each group. Finally, the tool allows determining the biological activity of each molecule by a voting scheme. The application of the D2-MCS tool was tested on a standardized, high quality dataset gathered from ChEMBL and have shown outperformance of our tool when compare to well-known single classification models