4 resultados para border development and integration

em Instituto Politécnico do Porto, Portugal


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We have developed a new method for single-drop microextraction (SDME) for the preconcentration of organochlorine pesticides (OCP) from complex matrices. It is based on the use of a silicone ring at the tip of the syringe. A 5 μL drop of n-hexane is applied to an aqueous extract containing the OCP and found to be adequate to preconcentrate the OCPs prior to analysis by GC in combination with tandem mass spectrometry. Fourteen OCP were determined using this technique in combination with programmable temperature vaporization. It is shown to have many advantages over traditional split/splitless injection. The effects of kind of organic solvent, exposure time, agitation and organic drop volume were optimized. Relative recoveries range from 59 to 117 %, with repeatabilities of <15 % (coefficient of variation) were achieved. The limits of detection range from 0.002 to 0.150 μg kg−1. The method was applied to the preconcentration of OCPs in fresh strawberry, strawberry jam, and soil.

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— In the new learning environments, built width digital technologies, the need to promote quality of education resources, commonly known as Learning Objects, which can support formal and informal distance learning, emerge as one of the biggest challenge that educational institutions will have to face. Due to the fact that is expensive, the reuse and sharing became very important issue. This article presents a Learning Object Repository which aims to store, to disseminate and maintain accessible Learning Objects.

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A new procedure for determining eleven organochlorine pesticides in soils using microwave-assisted extraction (MAE) and headspace solid phase microextraction (HS-SPME) is described. The studied pesticides consisted of mirex, α- and γ-chlordane, p,p’-DDT, heptachlor, heptachlor epoxide isomer A, γ-hexachlorocyclohexane, dieldrin, endrin, aldrine and hexachlorobenzene. The HS-SPME was optimized for the most important parameters such as extraction time, sample volume and temperature. The present analytical procedure requires a reduced volume of organic solvents and avoids the need for extract clean-up steps. For optimized conditions the limits of detection for the method ranged from 0.02 to 3.6 ng/g, intermediate precision ranged from 14 to 36% (as CV%), and the recovery from 8 up to 51%. The proposed methodology can be used in the rapid screening of soil for the presence of the selected pesticides, and was applied to landfill soil samples.

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An overwhelming problem in Math Curriculums in Higher Education Institutions (HEI), we are daily facing in the last decade, is the substantial differences in Math background of our students. When you try to transmit, engage and teach subjects/contents that your “audience” is unable to respond to and/or even understand what we are trying to convey, it is somehow frustrating. In this sense, the Math projects and other didactic strategies, developed through Learning Management System Moodle, which include an array of activities that combine higher order thinking skills with math subjects and technology, for students of HE, appear as remedial but important, proactive and innovative measures in order to face and try to overcome these considerable problems. In this paper we will present some of these strategies, developed in some organic units of the Polytechnic Institute of Porto (IPP). But, how “fruitful” are the endless number of hours teachers spent in developing and implementing these platforms? Do students react to them as we would expect? Do they embrace this opportunity to overcome their difficulties? How do they use/interact individually with LMS platforms? Can this environment that provides the teacher with many interesting tools to improve the teaching – learning process, encourages students to reinforce their abilities and knowledge? In what way do they use each available material – videos, interactive tasks, texts, among others? What is the best way to assess student’s performance in these online learning environments? Learning Analytics tools provides us a huge amount of data, but how can we extract “good” and helpful information from them? These and many other questions still remain unanswered but we look forward to get some help in, at least, “get some drafts” for them because we feel that this “learning analysis”, that tackles the path from the objectives to the actual results, is perhaps the only way we have to move forward in the “best” learning and teaching direction.