Building Capacity in Developing Countries : OER for Food Safety

The Food Safety Knowledge Network (FSKN) was developed through the collaboration of Michigan State University and a professional network of international food industry retailers and manufacturers. The key objective of the FSKN project is to provide technical resources, in a cost effective way, in order to promote food safety in developing countries and for small and less developed companies. FSKN uses a competency based model including a framework, OERs, and assessments. These tools are being used to support face-to-face training, fully online training, and to gauge the learning outcomes of a series of pilot groups which were held in India, Egypt, and China.

AgShare : Building Community and Content with Multiple Partners

Michigan State University and OER Africa are creating a win-win collaboration of existing organizations for African publishing, localizing, and sharing of teaching and learning materials that fill critical resource gaps in African MSc agriculture curriculum. By the end of the 18-month planning and pilot initiative, African agriculture universities, faculty, students, researchers, NGO leaders, extension staff, and farmers will participate in building AgShare by demonstrating its benefits and outcomes and by building momentum and support for growth.

Building a Manifesto for OER sustainability : UK experiences

Evidence of sustainability, or the potential to achieve this, is increasingly a pre-requisite for OER activity, whether imposed by funders, by institutions requiring a 'business case' for OER, or practitioners themselves - academics, educational technologists and librarians, concerned about how to justify engagement with a unfamiliar, and unproven practices, in today's climate of limited resource. However, it is not clear what is meant by 'sustainability' in relation to OER, what will be needed to achieve or demonstrate this, nor who the expectation of sustainability relates to. This paper draws on experiences of UK OER projects to identify aspirations that those involved in delivering OER activity have for OER sustainability ¿ what a 'manifesto' for OER sustainability beyond project funding, based on OER use, might look like.

Determinants of the educational use of digital learning materials: The mediating role of self-efficacy, perceived norm and attitude

Initiatives to stimulate the development and propagation of open educational resources (OER) need a sufficiently large community that can be mobilized to participate in this endeavour. Failure to achieve this could lead to underuse of OER. In the context of the Wikiwijs initiative a large scale survey was undertaken amongst primary and secondary school teachers to explore possible determinants of the educational use of digital learning materials (DLMs). Basing on the Integrative Model of Behaviour Prediction it was conjectured that self-efficacy, attitude and perceived norm would take a central role in explaining the intention to use DLMs. Several other predictors were added to the model as well whose effects were hypothesized to be mediated by the three central variables.All conjectured relationships were found using path analysis on survey data from 1484 teachers. Intention to DLMs was most strongly determined by self-efficacy, followed by attitude. ICT proficiency was in its turn the strongest predictor of self-efficacy. Perceived norm played only a limited role in the intention to use DLMs. Concluding, it seems paramount for the success of projects such as Wikiwijs to train teachers in the use of digital learning materials and ICT (e.g. the digital blackboard) and to impact on their attitude.

Using self organizing maps on compositional data

Self-organizing maps (Kohonen 1997) is a type of artificial neural network developedto explore patterns in high-dimensional multivariate data. The conventional versionof the algorithm involves the use of Euclidean metric in the process of adaptation ofthe model vectors, thus rendering in theory a whole methodology incompatible withnon-Euclidean geometries.In this contribution we explore the two main aspects of the problem:1. Whether the conventional approach using Euclidean metric can shed valid resultswith compositional data.2. If a modification of the conventional approach replacing vectorial sum and scalarmultiplication by the canonical operators in the simplex (i.e. perturbation andpowering) can converge to an adequate solution.Preliminary tests showed that both methodologies can be used on compositional data.However, the modified version of the algorithm performs poorer than the conventionalversion, in particular, when the data is pathological. Moreover, the conventional ap-proach converges faster to a solution, when data is \well-behaved".Key words: Self Organizing Map; Artificial Neural networks; Compositional data

Novel MLPA procedure using self-designed probes allows comprehensive analysis for CNVs of the genes involved in Hirschsprung disease.

Background: Hirschsprung disease is characterized by the absence of intramural ganglion cells in the enteric plexuses, due to a fail during enteric nervous system formation. Hirschsprung has a complex genetic aetiology and mutations in several genes have been related to the disease. There is a clear predominance of missense/nonsense mutations in these genes whereas copy number variations (CNVs) have been seldom described, probably due to the limitations of conventional techniques usually employed for mutational analysis. In this study, we have looked for CNVs in some of the genes related to Hirschsprung (EDNRB, GFRA1, NRTN and PHOX2B) using the Multiple Ligation-dependent Probe Amplification (MLPA) approach. Methods: CNVs screening was performed in 208 HSCR patients using a self-designed set of MLPA probes, covering the coding region of those genes. Results: A deletion comprising the first 4 exons in GFRA1 gene was detected in 2 sporadic HSCR patients and in silico approaches have shown that the critical translation initiation signal in the mutant gene was abolished. In this study, we have been able to validate the reliability of this technique for CNVs screening in HSCR. Conclusions: The implemented MLPA based technique presented here allows CNV analysis of genes involved in HSCR that have not been not previously evaluated. Our results indicate that CNVs could be implicated in the pathogenesis of HSCR, although they seem to be an uncommon molecular cause of HSCR.

Respiratory self-navigated postcontrast whole-heart coronary MR angiography: initial experience in patients.

PURPOSE: To assess the diagnostic performance of respiratory self-navigation for whole-heart coronary magnetic resonance (MR) angiography in a patient cohort referred for diagnostic cardiac MR imaging. MATERIALS AND METHODS: Written informed consent was obtained from all participants for this institutional review board-approved study. Self-navigated coronary MR angiography was performed after administration of a contrast agent in 78 patients (mean age, 48.5 years ± 20.7 [standard deviation]; 53 male patients) referred for cardiac MR imaging because of coronary artery disease (n = 40), cardiomyopathy (n = 14), congenital anomaly (n = 17), or "other" (n = 7). Examination duration was recorded, and the image quality for each coronary segment was assessed with consensus reading. Vessel sharpness, length, and diameter were measured. Quantitative values in proximal, middle, and distal segments were compared by using analysis of variance and t tests. A double-blinded comparison with the results of x-ray angiography was performed when such results were available. RESULTS: When patients with different indications for cardiac MR imaging were examined with self-navigated postcontrast coronary MR angiography, whole-heart data sets with 1.15-mm isotropic spatial resolution were acquired in an average of 7.38 minutes ± 1.85. The main and proximal coronary segments could be visualized in 92.3% of cases, while the middle and distal segments could be visualized in 84.0% and 55.8% of cases, respectively. Subjective scores and vessel sharpness were significantly higher in the proximal segments than in the middle and distal segments (P < .05). Anomalies of the coronary arteries could be confirmed or excluded in all cases. Per-vessel sensitivity and specificity for stenosis detection were 64.7% and 85.0%, respectively, in the 31 patients for whom reference standard x-ray coronary angiography results were available. CONCLUSION: The self-navigated coronary MR angiography sequence shows promise for coronary imaging. However, technical improvements are needed to improve image quality, especially in the more distal coronary segments.

Automatic self-configuration of the logical network using distributed software agents

We present a system for dynamic network resource configuration in environments with bandwidth reservation. The proposed system is completely distributed and automates the mechanisms for adapting the logical network to the offered load. The system is able to manage dynamically a logical network such as a virtual path network in ATM or a label switched path network in MPLS or GMPLS. The system design and implementation is based on a multi-agent system (MAS) which make the decisions of when and how to change a logical path. Despite the lack of a centralised global network view, results show that MAS manages the network resources effectively, reducing the connection blocking probability and, therefore, achieving better utilisation of network resources. We also include details of its architecture and implementation

Prevalent role of TCR alpha-chain in the selection of the preimmune repertoire specific for a human tumor-associated self-antigen.

The specificity of recognition of pMHC complexes by T lymphocytes is determined by the V regions of the TCR alpha- and beta-chains. Recent experimental evidence has suggested that Ag-specific TCR repertoires may exhibit a more V alpha- than V beta-restricted usage. Whether V alpha usage is narrowed during immune responses to Ag or if, on the contrary, restricted V alpha usage is already defined at the early stages of TCR repertoire selection, however, has remained unexplored. Here, we analyzed V and CDR3 TCR regions of single circulating naive T cells specifically detected ex vivo and isolated with HLA-A2/melan-A peptide multimers. Similarly to what was previously observed for melan-A-specific Ag-experienced T cells, we found a relatively wide V beta usage, but a preferential V alpha 2.1 usage. Restricted V alpha 2.1 usage was also found among single CD8(+) A2/melan-A multimer(+) thymocytes, indicating that V alpha-restricted selection takes place in the thymus. V alpha 2.1 usage, however, was independent from functional avidity of Ag recognition. Thus, interaction of the pMHC complex with selected V alpha-chains contributes to set the broad Ag specificity, as underlined by preferential binding of A2/melan-A multimers to V alpha 2.1-bearing TCRs, whereas functional outcomes result from the sum of these with other interactions between pMHC complex and TCR.

Self-Navigation with Compressed Sensing for 2D Translational Motion Correction in Free-Breathing Coronary MRI: A Feasibility Study.

PURPOSE: Respiratory motion correction remains a challenge in coronary magnetic resonance imaging (MRI) and current techniques, such as navigator gating, suffer from sub-optimal scan efficiency and ease-of-use. To overcome these limitations, an image-based self-navigation technique is proposed that uses "sub-images" and compressed sensing (CS) to obtain translational motion correction in 2D. The method was preliminarily implemented as a 2D technique and tested for feasibility for targeted coronary imaging. METHODS: During a 2D segmented radial k-space data acquisition, heavily undersampled sub-images were reconstructed from the readouts collected during each cardiac cycle. These sub-images may then be used for respiratory self-navigation. Alternatively, a CS reconstruction may be used to create these sub-images, so as to partially compensate for the heavy undersampling. Both approaches were quantitatively assessed using simulations and in vivo studies, and the resulting self-navigation strategies were then compared to conventional navigator gating. RESULTS: Sub-images reconstructed using CS showed a lower artifact level than sub-images reconstructed without CS. As a result, the final image quality was significantly better when using CS-assisted self-navigation as opposed to the non-CS approach. Moreover, while both self-navigation techniques led to a 69% scan time reduction (as compared to navigator gating), there was no significant difference in image quality between the CS-assisted self-navigation technique and conventional navigator gating, despite the significant decrease in scan time. CONCLUSIONS: CS-assisted self-navigation using 2D translational motion correction demonstrated feasibility of producing coronary MRA data with image quality comparable to that obtained with conventional navigator gating, and does so without the use of additional acquisitions or motion modeling, while still allowing for 100% scan efficiency and an improved ease-of-use. In conclusion, compressed sensing may become a critical adjunct for 2D translational motion correction in free-breathing cardiac imaging with high spatial resolution. An expansion to modern 3D approaches is now warranted.