959 resultados para Corpus-based Translation Studies


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The idiomatic expression “In Rome be a Roman” can be applied to leadership training and development as well. Leaders who can act as role models inspire other future leaders in their behaviour, attitudes and ways of thinking. Based on two examples of current leaders in the fields of Politics and Public Administration, I support the idea that exposure to role models during their training was decisive for their career paths and current activities as prominent characters in their profession. Issues such as how students should be prepared for community or national leadership as well as cross-cultural engagement are raised here. The hypothesis of transculturalism and cross-cultural commitment as a factor of leadership is presented. Based on current literature on Leadership as well as the presented case studies, I expect to raise a debate focusing on strategies for improving leaders’ training in their cross-cultural awareness.

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The conjugation of antigens with ligands of pattern recognition receptors (PRR) is emerging as a promising strategy for the modulation of specific immunity. Here, we describe a new Escherichia coli system for the cloning and expression of heterologous antigens in fusion with the OprI lipoprotein, a TLR ligand from the Pseudomonas aeruginosa outer membrane (OM). Analysis of the OprI expressed by this system reveals a triacylated lipid moiety mainly composed by palmitic acid residues. By offering a tight regulation of expression and allowing for antigen purification by metal affinity chromatography, the new system circumvents the major drawbacks of former versions. In addition, the anchoring of OprI to the OM of the host cell is further explored for the production of novel recombinant bacterial cell wall-derived formulations (OM fragments and OM vesicles) with distinct potential for PRR activation. As an example, the African swine fever virus ORF A104R was cloned and the recombinant antigen was obtained in the three formulations. Overall, our results validate a new system suitable for the production of immunogenic formulations that can be used for the development of experimental vaccines and for studies on the modulation of acquired immunity.

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The development of renewable energy sources and Distributed Generation (DG) of electricity is of main importance in the way towards a sustainable development. However, the management, in large scale, of these technologies is complicated because of the intermittency of primary resources (wind, sunshine, etc.) and small scale of some plants. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. VPPs can ensure a secure, environmentally friendly generation and optimal management of heat, electricity and cold as well as optimal operation and maintenance of electrical equipment, including the sale of electricity in the energy market. For attaining these goals, there are important issues to deal with, such as reserve management strategies, strategies for bids formulation, the producers’ remuneration, and the producers’ characterization for coalition formation. This chapter presents the most important concepts related with renewable-based generation integration in electricity markets, using VPP paradigm. The presented case studies make use of two main computer applications:ViProd and MASCEM. ViProd simulates VPP operation, including the management of plants in operation. MASCEM is a multi-agent based electricity market simulator that supports the inclusion of VPPs in the players set.

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Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. Each agent has the knowledge about a different method for defining a strategy for playing in the market, the main agent chooses the best among all those, and provides it to the market player that requests, to be used in the market. This paper also presents a methodology to manage the efficiency/effectiveness balance of this method, to guarantee that the degradation of the simulator processing times takes the correct measure.

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Presently power system operation produces huge volumes of data that is still treated in a very limited way. Knowledge discovery and machine learning can make use of these data resulting in relevant knowledge with very positive impact. In the context of competitive electricity markets these data is of even higher value making clear the trend to make data mining techniques application in power systems more relevant. This paper presents two cases based on real data, showing the importance of the use of data mining for supporting demand response and for supporting player strategic behavior.

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Ensuring sustainable development conditions is presently world widely recognized as a critically important goal. This makes the use of electricity generation technologies based on renewable energy sources very relevant. Developing countries depend on an adequate availability of electrical energy to assure economic progress and are usually characterized by a high increase in electricity consumption. This makes sustainable development a huge challenge but it can also be taken as an opportunity, especially for countries which do not have fossil resources. This paper presents a study concerning the expansion of an already existent wind farm, located in Praia, the capital of Cape Verde Republic. The paper includes results from simulation studies that have been undertaken using PSCAD software and some economic considerations.

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This paper studies musical opus from the point of view of three mathematical tools: entropy, pseudo phase plane (PPP), and multidimensional scaling (MDS). The experiments analyze ten sets of different musical styles. First, for each musical composition, the PPP is produced using the time series lags captured by the average mutual information. Second, to unravel hidden relationships between the musical styles the MDS technique is used. The MDS is calculated based on two alternative metrics obtained from the PPP, namely, the average mutual information and the fractal dimension. The results reveal significant differences in the musical styles, demonstrating the feasibility of the proposed strategy and motivating further developments towards a dynamical analysis of musical sounds.

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This essay suggests that the intersubjectivity in translation should be given priority because different stages of the translation activity have different subjects, and presents a practical intersubjective ethics of translation based on an interpretation of the intersubjective relations connected with translation activities in a perspective of game theory in the hope that it can equip us with better explanations of the translator’s calculations or considerations in the professional practice.

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Valproic acid (2-propyl pentanoic acid) is a pharmaceutical drug used for treatment of epileptic seizures absence, tonic-clonic (grand mal), complex partial seizures, and mania in bipolar disorder [1]. Valproic acid is a slightly soluble in water and therefore as active pharmaceutical ingredient it is most commonly applied in form of sodium or magnesium valproate salt [1].However the list of adverse effects of these compounds is large and includes among others: tiredness, tremor, sedation and gastrointestinal disturbances [2]. Ionic liquids (ILs) are promising compounds as Active Pharmaceutical Ingredients (APIs)[3]. In this context, the combinations of the valproate anion with appropriate cation when ILs and salts are formed can significantly alter valproate physical, chemical and thermal properties.[4] This methodology can be used for drug modification (alteration of drug solubility in water, lipids, bioavailability, etc)[2] and therefore can eliminate some adverse effect of the drugs related to drug toxicity due for example to its solubility in water and lipids (interaction with intestines). Herein, we will discuss the development of ILs based on valproate anion (Figure 1) prepared according a recent optimized and sustainable acid-base neutralization method [4]. The organic cations such as cetylpyridinium, choline and imidazolium structures were selected based on their biocompatibility and recent applications in pharmacy [3]. All novel API-ILs based on valproate have been studied in terms of their physical, chemical (viscosity, density, solubility) and thermal (calorimetric studies) properties as well as their biological activity.

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In recent years Ionic Liquids (ILs) are being applied in life sciences. ILs are being produce with active pharmaceutical drugs (API) as they can reduce polymorphism and drug solubility problems [1] Also ILs are being applied as a drug delivery device in innovative therapies What is appealing in ILs is the ILs building up platform, the counter-ion can be carefully chosen in order to avoid undesirable side effects or to give innovative therapies in which two active ions are paired. This work shows ILs based on ampicillin (an anti-bacterial agent) and ILs based on Amphotericin B. Also we show studies that indicate that ILs based on Ampicillin could reverse resistance in some bacteria. The ILs produced in this work were synthetized by the neutralization method described in Ferraz et. al. [2] Ampicillin anion was combined with the following organic cations 1-ethyl-3-methylimidazolium, [EMIM]; 1-hydroxy-ethyl-3-methylimidazolium, [C2OHMIM]; choline, [cholin]; tetraethylammonium, [TEA]; cetylpyridinium, [C16pyr] and trihexyltetradecylphosphonium, [P6,6,6,14]. Amphotericin B was combined with [C16pyr], [cholin] and 1-metohyethyl-3-methylimidazolium, [C3OMIM]. The ILs-APIs based on ampicillin[2] were tested against sensitive Gram-negative bacteria Escherichia coli ATCC 25922 and Klebsiella pneumonia (clinical isolated), as well as on Gram positive Staphylococcus Aureus ATCC 25923, Staphylococcus epidermidis and Enterococcus faecalis. The arising resistance developed by bacteria to antibiotics is a serious public health threat and needs new and urgent measures. We study the bacterial activity of these compounds against a panel of resistant bacteria (clinical isolated strains): E. coli CTX M9, E. coli TEM CTX M9, E. coli TEM1, E. coli CTX M2, E. coli AmpC Mox2. In this work we demonstrate that is possible to produce ILs from anti-bacterial and anti-fungal compounds. We show here that the new ILs can reverse the bacteria resistance. With the careful choice of the organic cation, it is possible to create important biological and physic-chemical properties. This work also shows that the ion-pair is fundamental in ampicillin mechanism of action.

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Water-based cellulose cholesteric liquid crystalline phases at rest can undergo structural changes induced by shear flow. This reflects on the deuterium spectra recorded when the system is investigated by rheo-nuclear magnetic resonance (rheo-NMR) techniques. In this work, the model system hydroxypropylcellulose (HPC)+water is revisited using rheo-NMR to clarify unsettled points regarding its behavior under shear and in relaxation. The NMR spectra allow the identification of five different stable ordering states, within shear and relaxation, which are well integrated in a mesoscopic picture of the system's structural evolution under shear and relaxation. This picture emerging from the large body of studies available for this system by other experimental techniques, accounts well for the NMR data and is in good agreement with the three distinct regions of steady shear flow recognized for some lyotropic LC polymers. Shear rates in between 0.1 and 1.0 s(-1) where investigated using a Taylor-Couette flow and deuterated water was used as solvent for the deuterium NMR (DNMR) analysis.

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OBJECTIVE: A cross-sectional population-based study was conducted to assess, in active smokers, the relationship of number of cigarettes smoked and other characteristics to salivary cotinine concentrations. METHODS: A random sample of active smokers aged 15 years or older was selected using a stepwise cluster sample strategy, in the year 2000 in Rio de Janeiro, Brazil. The study included 401 subjects. Salivary cotinine concentration was determined using gas chromatography with nitrogen-phosphorus detection. A standard questionnaire was used to collect demographic and smoking behavioral data. The relation between the number of cigarettes smoked in the last 24h and cotinine level was examined by means of a nonparametric fitting technique of robust locally weighted regression. RESULTS: Significantly (p<0.05) higher adjusted mean cotinine levels were found in subjects smoking their first cigarette within five minutes after waking up, and in those smoking 1-20 cigarettes in the last 24h who reported inhaling more than ½ the time. In those smoking 1-20 cigarettes, the slope was significantly higher for those subjects waiting for more than five minutes before smoking their first cigarette after waking up, and those smoking "light" cigarettes when compared with their counterparts. These heterogeneities became negligible and non-significant when subjects with cotinine >40 ng/mL per cigarette were excluded. CONCLUSIONS: There was found a positive association between self-reporting smoking five minutes after waking up, and inhaling more than ½ the time are consistent and higher cotinine levels. These can be markers of dependence and higher nicotine intake. Salivary cotinine proved to be a useful biomarker of recent smoking and can be used in epidemiological studies and smoking cessation programs.

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OBJECTIVE: To assess the association between regular physical activity in adolescence and leisure-time physical activity in adulthood, with emphasis on gender differences. METHODS: A population-based cross-sectional study was carried out in Pelotas, Southern Brazil, in 2003. A representative sample of households was selected in multiple stages and subjects aged 20-59 years were interviewed. Leisure-time physical activity was evaluated using the International Physical Activity Questionnaire. Data on adolescent physical activity were based on subjects' recall. RESULTS: Of 2,577 subjects interviewed, 27.5% were classified as adequately active, and 54.9% reported regular physical activity in adolescence. Subjects who engaged in regular physical activity during adolescence were more likely to be adequately active in adulthood (adjusted prevalence ratio 1.42; 95% CI: 1.23; 1.65). This effect was stronger in women (adjusted prevalence ratio: 1.51; 95% CI: 1.22; 1.86) than men (adjusted prevalence ratio: 1.35; 95% CI: 1.10; 1.67). CONCLUSIONS: Promoting physical activity in school age may be a successful intervention against the epidemic of adult inactivity. Although women were less likely to report regular physical activity in adolescence, the effect of this experience on adult behavior was stronger than in men.

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Purpose: The aim of this paper is to promote qualitative methodology within the scientific community of management. The specific objective is oriented to propose an empirical research process based on case study method. This is to ensure rigor in the empirical research process, that future research may follow a similar procedure to that is proposed. Design/methodology/approach: Following a qualitative methodological approach, we propose a research process that develops according to four phases, each with several stages. This study analyses the preparatory and field work phases and their stages. Findings: The paper shows the influence that case studies have on qualitative empirical research process in management. Originality/value:. Case study method assumes an important role within qualitative research by allowing for the study and analysis of certain types of phenomena that occur inside organisations, and in respect of which quantitative studies cannot provide an answer.

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In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.