Standards and specifications to manage accessibility issues in e-learning

Despite the acknowledged need of providing a personalized and adaptive learning process for all, current learning management systems do not properly cover personalization and accessibility issues and they are still struggling to support the reusability requirements coming from the pervasive usage of standards. There is a lack of frameworks for providing layered-based infrastructure covering the interoperability required to manage the whole range of standards, applications and services needed to meet accessibility and adaptations needs of lifelong learning services.

Physiological features of Schizosaccharomyces pombe of interest in the making of white wines

This work studies the physiology of Schizosaccharomyces pombe strain 938 in the production of white wine with high malic acid levels as the sole fermentative yeast, as well as in mixed and sequential fermentations with Saccharomyces cerevisiae Cru Blanc. The induction of controlled maloalcoholic fermentation through the use of Schizosaccharomyces spp. is now being viewed with much interest. The acetic, malic and pyruvic acid concentrations, relative density and pH of the musts were measured over the entire fermentation period. In all fermentations in which Schizo. pombe 938 was involved, nearly all the malic acid was consumed and moderate acetic concentrations produced. The urea content and alcohol level of these wines were notably lower than in those made with Sacch. cerevisiae Cru Blanc alone. The pyruvic acid concentration was significantly higher in Schizo. pombe fermentations. The sensorial properties of the different final wines varied widely.

Crowdsourcing malaria parasite quantification: an online game for analyzing images of infected thick blood smears

Background: There are 600,000 new malaria cases daily worldwide. The gold standard for estimating the parasite burden and the corresponding severity of the disease consists in manually counting the number of parasites in blood smears through a microscope, a process that can take more than 20 minutes of an expert microscopist’s time. Objective: This research tests the feasibility of a crowdsourced approach to malaria image analysis. In particular, we investigated whether anonymous volunteers with no prior experience would be able to count malaria parasites in digitized images of thick blood smears by playing a Web-based game. Methods: The experimental system consisted of a Web-based game where online volunteers were tasked with detecting parasites in digitized blood sample images coupled with a decision algorithm that combined the analyses from several players to produce an improved collective detection outcome. Data were collected through the MalariaSpot website. Random images of thick blood films containing Plasmodium falciparum at medium to low parasitemias, acquired by conventional optical microscopy, were presented to players. In the game, players had to find and tag as many parasites as possible in 1 minute. In the event that players found all the parasites present in the image, they were presented with a new image. In order to combine the choices of different players into a single crowd decision, we implemented an image processing pipeline and a quorum algorithm that judged a parasite tagged when a group of players agreed on its position. Results: Over 1 month, anonymous players from 95 countries played more than 12,000 games and generated a database of more than 270,000 clicks on the test images. Results revealed that combining 22 games from nonexpert players achieved a parasite counting accuracy higher than 99%. This performance could be obtained also by combining 13 games from players trained for 1 minute. Exhaustive computations measured the parasite counting accuracy for all players as a function of the number of games considered and the experience of the players. In addition, we propose a mathematical equation that accurately models the collective parasite counting performance. Conclusions: This research validates the online gaming approach for crowdsourced counting of malaria parasites in images of thick blood films. The findings support the conclusion that nonexperts are able to rapidly learn how to identify the typical features of malaria parasites in digitized thick blood samples and that combining the analyses of several users provides similar parasite counting accuracy rates as those of expert microscopists. This experiment illustrates the potential of the crowdsourced gaming approach for performing routine malaria parasite quantification, and more generally for solving biomedical image analysis problems, with future potential for telediagnosis related to global health challenges.

Effect of misorientation on the compression of highly anisotropic single-crystal micropillars

The effect of crystal misorientation, geometrical tilt, and contact misalignment on the compression of highly anisotropic single crystal micropillars was assessed by means of crystal plasticity finite element simulations. The investigation was focused in single crystals with the NaCl structure, like MgO or LiF, which present a marked plastic anisotropy as a result of the large difference in the critical resolved shear stress between the “soft” {110}〈110〉 and the “hard” {100}〈110〉 active slip systems. It was found that contact misalignment led to a large reduction in the initial stiffness of the micropillar in crystals oriented in the soft and hard direction. The crystallographic tilt did not modify, however, the initial crystal stiffness. From the viewpoint of the plastic response, none of the effects analyzed led to significant differences in the flow stress when the single crystals were oriented along the “soft” [100] direction. Large differences were found, however, if the single crystal was oriented in the “hard” [111] direction as a result of the activation of the soft slip system. Numerical simulations were in very good agreement with experimental literature data.

Evaluating a web-based clinical decision support system for language disorders screening in a nursery school

Background: Early and effective identification of developmental disorders during childhood remains a critical task for the international community. The second highest prevalence of common developmental disorders in children are language delays, which are frequently the first symptoms of a possible disorder. Objective: This paper evaluates a Web-based Clinical Decision Support System (CDSS) whose aim is to enhance the screening of language disorders at a nursery school. The common lack of early diagnosis of language disorders led us to deploy an easy-to-use CDSS in order to evaluate its accuracy in early detection of language pathologies. This CDSS can be used by pediatricians to support the screening of language disorders in primary care. Methods: This paper details the evaluation results of the ?Gades? CDSS at a nursery school with 146 children, 12 educators, and 1 language therapist. The methodology embraces two consecutive phases. The first stage involves the observation of each child?s language abilities, carried out by the educators, to facilitate the evaluation of language acquisition level performed by a language therapist. Next, the same language therapist evaluates the reliability of the observed results. Results: The Gades CDSS was integrated to provide the language therapist with the required clinical information. The validation process showed a global 83.6% (122/146) success rate in language evaluation and a 7% (7/94) rate of non-accepted system decisions within the range of children from 0 to 3 years old. The system helped language therapists to identify new children with potential disorders who required further evaluation. This process will revalidate the CDSS output and allow the enhancement of early detection of language disorders in children. The system does need minor refinement, since the therapists disagreed with some questions from the CDSS knowledge base (KB) and suggested adding a few questions about speech production and pragmatic abilities. The refinement of the KB will address these issues and include the requested improvements, with the support of the experts who took part in the original KB development. Conclusions: This research demonstrated the benefit of a Web-based CDSS to monitor children?s neurodevelopment via the early detection of language delays at a nursery school. Current next steps focus on the design of a model that includes pseudo auto-learning capacity, supervised by experts.