Impact of the intrinsic motivation on the academic performance through voluntary assignments: An empirical analysis

The students academic performance is a key aspect for all agents involved in a higher education quality program. However, there is no unanimity on how to measure it. Some professionals choose assessing only cognitive aspects while others lean towards assessing the acquisition of certain skills. The need to train increasingly adapted professionals in order to respond to the companies’ demands and being able to compete internationally in a global labour market requires a kind of training that goes beyond memorizing. Critical and logical thinking are amongst written language skills demanded in the field of Social Sciences. The objective of this study is to empirically demonstrate the impact of voluntary assignments on the academic performance of students. Our hypothesis is that students who complete high quality voluntary assignments are those more motivated and, therefore, those with higher grades. An experiment with students from the "Financial Accounting II" during the academic year of 2012/13 at the Business and Economics School of the UCM was carried out. A series of voluntary assessments involving the preparation of accounting essays were proposed in order to develop skills and competencies as a complement to the lessons included in the curriculum of the subject. At the end of the course, the carrying-out or not of the essay together with its critical, reflective quality and style, were compared. Our findings show a relationship between the voluntarily presented papers of quality and the final grade obtained throughout the course. These results show that the students intrinsic motivation is a key element in their academic performance. On the other hand, the teachers role focuses on being a motivating element through the learning process.

Applying a QSPR correlation to the prediction of surface tensions of ionic liquids

Ionic liquids (ILs) have attracted large amount of interest due to their unique properties. Although large effort has been focused on the investigation of their potential application, characterization of ILs properties and structure–property relationships of ILs are poorly understood. Computer aided molecular design (CAMD) of ionic liquids (ILs) can only be carried if predictive computational methods for the ILs properties are available. The limited availability of experimental data and their quality have been preventing the development of such tools. Based on experimental surface tension data collected from the literature and measured at our laboratory, it is here shown how a quantitative structure–property relationship (QSPR) correlation for parachors can be used along with an estimation method for the densities to predict the surface tensions of ILs. It is shown that a good agreement with literature data is obtained. For circa 40 ionic liquids studied a mean percent deviation (MPD) of 5.75% with a maximum deviation inferior to 16% was observed. A correlation of the surface tensions with the molecular volumes of the ILs was developed for estimation of the surface tensions at room temperature. It is shown that it can describe the experimental data available within a 4.5% deviation. The correlations here developed can thus be used to evaluate the surface tension of ILs for use in process design or in the CAMD of new ionic liquids.

Estimation of speed of sound of ionic liquids using surface tensions and densities: A volume based approach

The limited availability of experimental data and their quality have been preventing the development of predictive methods and Computer Aided Molecular Design (CAMD) of ionic liquids (ILs). Based on experimental speed of sound data collected from the literature, the inter-relationship of surface tension (s), density (?), and speed of sound (u) has been examined for imidazolium based ILs containing hexafluorophosphate (PF6), tetrafluoroborate (BF4), bis(trifluoromethanesulphonyl) amide (NTf2), methyl sulphate (MeSO4), ethyl sulphate (EtSO4), and trifluoromethanesulphonate (CF3SO3) anions, covering wide ranges of temperature, 278.15–343.15 K and speed of sound, 1129.0–1851.0 m s-1. The speed of sound was correlated with a modified Auerbach's relation, by using surface tension and density data obtained from volume based predictive methods previously proposed by the authors. It is shown that a good agreement with literature data is obtained. For 133 data points of 14 ILs studied a mean percent deviation (MPD) of 1.96% with a maximum deviation inferior to 5% was observed. The correlations developed here can thus be used to evaluate the speeds of sound of new ionic liquids.

Software project initiation and planning – an empirical study

This study describes a study of 14 software companies, on how they initiate and pre-plan software projects. The aim was to obtain an indication of the range of planning activities carried out. The study, using a convenience sample, was carried out using structured interviews, with questions about early software project planning activities. The study offers evidence that an iterative and incremental development process presents extra difficulties in the case of fixed-contract projects. The authors also found evidence that feasibility studies were common, but generally informal in nature. Documentation of the planning process, especially for project scoping, was variable. For incremental and iterative development projects, an upfront decision on software architecture was shown to be preferred over allowing the architecture to just ‘emerge’. There is also evidence that risk management is recognised but often performed incompletely. Finally appropriate future research arising from the study is described.

Joined Spectral Trees for Scalable SPIHT-Based Multispectral Image Compression

In this paper, the compression of multispectral images is addressed. Such 3-D data are characterized by a high correlation across the spectral components. The efficiency of the state-of-the-art wavelet-based coder 3-D SPIHT is considered. Although the 3-D SPIHT algorithm provides the obvious way to process a multispectral image as a volumetric block and, consequently, maintain the attractive properties exhibited in 2-D (excellent performance, low complexity, and embeddedness of the bit-stream), its 3-D trees structure is shown to be not adequately suited for 3-D wavelet transformed (DWT) multispectral images. The fact that each parent has eight children in the 3-D structure considerably increases the list of insignificant sets (LIS) and the list of insignificant pixels (LIP) since the partitioning of any set produces eight subsets which will be processed similarly during the sorting pass. Thus, a significant portion from the overall bit-budget is wastedly spent to sort insignificant information. Through an investigation based on results analysis, we demonstrate that a straightforward 2-D SPIHT technique, when suitably adjusted to maintain the rate scalability and carried out in the 3-D DWT domain, overcomes this weakness. In addition, a new SPIHT-based scalable multispectral image compression algorithm is used in the initial iterations to exploit the redundancies within each group of two consecutive spectral bands. Numerical experiments on a number of multispectral images have shown that the proposed scheme provides significant improvements over related works.

Development of a novel PCR assay for the identification of the black yeast, Exophiala (Wangiella) dermatitidis from adult patients with cystic fibrosis (CF)

Cystic fibrosis (CF) patients may suffer increased morbidity and mortality through colonisation, allergy and invasive infection from fungi. The black yeast, Exophiala dermatitidis (synonym Wangiella dermatitidis) has been found with increasing frequency in sputum specimens of CF patients, with reported isolation rates ranging from 1.1 to 15.7%. At present, no diagnostic PCR exists to aid with the clinical laboratory detection and identification of this organism. A novel species-specific PCR-based assay was developed for the detection of E. dermatitidis, based on employment of rDNA operons and interspacer (ITS) regions between these rDNA operons. Two novel primers, (designated ExdF & ExdR) were designed in silico with the aid of computer-aided alignment software and with the alignment of multiple species of Exophiala, as well as with other commonly described yeasts and filamentous fungi within CF sputum, including Candida. Aspergillus and Scedosporium. An amplicon of approximately 455 by was generated, spanning the partial ITS I region - the complete 5.8S rDNA region - partial ITS2 region, employing ExdF (forward primer [16-mer], 5'-CCG CCT ATT CAG GTC C-3' and ExdR (reverse primer [16-mer], 5'-TCT CTC CCA CTC CCG C-3', was employed and optimised on extracted genomic DNA from a well characterised culture of E. dermatitidis, as well as with high quality genomic DNA template from a further 16 unrelated fungi, including Candida albicans, C. dubliniensis, C. parapsilosis, C. glabrata, Scedosporium apiospermum, Penicillium sp., Aspergillus fumigatus, Aspergillus versicolor, Pichia guilliermondii, Rhodotorula sp., Trichosporon sp., Aureobasidium pullulans, Fusarium sp., Mucor hiemalis, Bionectria ochroleuca, Gibberella pulicaris. Results demonstrated that only DNA from E. dermatitidis gave an amplification product of the expected sire, whilst none of the other fungi were amplifiable. Subsequent employment of this primer pair detected this yeast from mycological cultures from 2/50 (4%) adult CF patients. These two patients were the only patients who were previously shown to have a cultural history of E. dermatitidis from their sputum. E. dermatitidis is a slow-growing fungus, which usually takes up to two weeks to culture in the microbiology laboratory and therefore is slow to detect conventionally, with the risk of bacterial overgrowth from common co-habiting pan- and multiresistant bacterial pathogens from sputum. namely Pseudomonas aeruginosa and Burkholderia cepacia complex organisms, hence this species-specific PCR assay may help detect this organism from CF sputum more specifically and rapidly. Overall, employment of this novel assay nay help in the understanding of the occurrence. aetiology and epidemiology of E. dermatitidis, as an emerging fungal agent in patients with CF. (C) 2008 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

Using Virtual Reality to Analyze Sports Performance

Improving performance in sports requires a better understanding of the perception-action loop employed by athletes. Because of its inherent limitations, video playback doesn't permit this type of in-depth analysis. Interactive, immersive virtual reality can overcome these limitations and foster a better understanding of sports performance.

Rhodopsin and the Others: A Historical Perspective on Structural Studies of G Protein-Coupled Receptors

The role of rhodopsin as a structural prototype for the study of the whole superfamily of G protein-coupled receptors (GPCRs) is reviewed in an historical perspective. Discovered at the end of the nineteenth century, fully sequenced since the early 1980s, and with direct three-dimensional information available since the 1990s, rhodopsin has served as a platform to gather indirect information on the structure of the other superfamily members. Recent breakthroughs have elicited the solution of the structures of additional receptors, namely the beta 1- and beta 2-adrenergic receptors and the A(2A) adenosine receptor, now providing an opportunity to gauge the accuracy of homology modeling and molecular docking techniques and to perfect the computational protocol. Notably, in coordination with the solution of the structure of the A(2A) adenosine receptor, the first "critical assessment of GPCR structural modeling and docking" has been organized, the results of which highlighted that the construction of accurate models, although challenging, is certainly achievable. The docking of the ligands and the scoring of the poses clearly emerged as the most difficult components. A further goal in the field is certainly to derive the structure of receptors in their signaling state, possibly in complex with agonists. These advances, coupled with the introduction of more sophisticated modeling algorithms and the increase in computer power, raise the expectation for a substantial boost of the robustness and accuracy of computer-aided drug discovery techniques in the coming years.

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

Binding modes of diketo-acid inhibitors of HIV-1 integrase: A comparative molecular dynamics simulation study

HIV-1 integrase (IN) has become an attractive target since drug resistance against HIV-1 reverse transcriptase (RT) and protease (PR) has appeared. Diketo acid (DKA) inhibitors are potent and selective inhibitors of HIV-1 IN: however the action mechanism is not well understood. Here, to study the inhibition mechanism of DKAs we performed 10 ns comparative molecular dynamics simulations on HIV-1 IN bound with three most representative DMA inhibitors: Shionogi inhibitor, S-1360 and two Merck inhibitors L-731,988 and L-708,906. Our simulations show that the acidic part of S-1360 formed salt bridge and cation-pi interactions with Lys159. In addition, the catalytic Glu152 in S-1360 was pushed away from the active site to form an ion-pair interaction with Arg199. The Merck inhibitors can maintain either one or both of these ion-pair interaction features. The difference in potencies of the DMA inhibitors is thus attributed to the different binding modes at the catalytic site. Such structural information at atomic level, not only demonstrates the action modes of DMA inhibitors but also provides a novel starting point for structural-based design of HIV-1 IN inhibitors.