Designing collaborative,constructionist and contextual applications for handheld devices

This paper explores current applications for handheld devices and questions which of these make full use of the unique attributes of handheld devices in order to facilitate learning in a pedagogically sensible manner. In order to do so, the paper presents a functional framework which analyses handheld application in relation to their use as well as the pedagogical underpinning, if any, that informs their development. Our framework currently consists of seven distinct categories of application, which we term: administrative, referential, interactive, microworld, data collection, location aware and collaborative. We argue that three categories, namely data collection, location aware and collaborative, are particularly suited to learning with handheld devices when they are informed by collaborative, contextual and constructionist learning theories. Furthermore, we contend that applications of the type just outlined deserve further research since they are not attempting to replicate, or even augment, existing learning scenarios but rather they try to create new learning opportunities which would not be possible without (mobile) technology. Finally, the authors introduce a number of applications and learning scenarios that they have developed for handheld devices and explain their position within the framework.     

Characterizing Strong Stability Preserving Additive Runge-Kutta Methods

Space discretization of some time dependent partial differential equations give rise to ordinary differential equations containing additive terms with different stiffness properties. In these situations, additive Runge-Kutta (additive RK) methods are used. For additive RK methods the curve of absolute monotonicity gives stepsize restrictions for monotonicity. Necessary conditions for nontrivial curves of absolute monotonicity are the nonnegativity of the additive RK coefficients and some inequalities on some incidence matrices. In this paper we characterize strong stability preserving additive Runge-Kutta methods giving some order barriers and structural properties. Research supported by the Ministerio de Educación y Ciencia, Project MTM2005-03894.     

Engineered Neutral Phosphorous Dendrimers Protect Mouse Cortical Neurons and Brain Organoids from Excitotoxic Death

Nanoparticles are playing an increasing role in biomedical applications. Excitotoxicity plays a significant role in the pathophysiology of neurodegenerative diseases, such as Alzheimer’s or Parkinson’s disease. Glutamate ionotropic receptors, mainly those activated by N-methyl-D-aspartate (NMDA), play a key role in excitotoxic death by increasing intraneuronal calcium levels; triggering mitochondrial potential collapse; increasing free radicals; activating caspases 3, 9, and 12; and inducing endoplasmic reticulum stress. Neutral phosphorous dendrimers, acting intracellularly, have neuroprotective actions by interfering with NMDA-mediated excitotoxic mechanisms in rat cortical neurons. In addition, phosphorous dendrimers can access neurons inside human brain organoids, complex tridimensional structures that replicate a significant number of properties of the human brain, to interfere with NMDA-induced mechanisms of neuronal death. Phosphorous dendrimers are one of the few nanoparticles able to gain access to the inside of neurons, both in primary cultures and in brain organoids, and to exert pharmacological actions by themselves.     

Influence of β‐nucleation on polymorphism and properties in random copolymers and terpolymers of propylene

The competition between α, β, and γ polymorphs has been studied in several random copolymers and terpolymers of propylene, by performing X‐ray diffraction and differential scanning calorimetry experiments. Formation of β‐crystals, achieved by the addition of a β‐nucleating agent, was found to be highly dependent on comonomer type and crystallization conditions. Additionally, the mechanical properties have been evaluated from stress‐strain, microhardness and dynamic‐mechanical thermal analyses. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers     

Semi-automated and fully automated mammographic density measurement and breast cancer risk prediction

The task of breast density quantification is becoming increasingly relevant due to its association with breast cancer risk. In this work, a semi-automated and a fully automated tools to assess breast density from full-field digitized mammograms are presented. The first tool is based on a supervised interactive thresholding procedure for segmenting dense from fatty tissue and is used with a twofold goal: for assessing mammographic density (MD) in a more objective and accurate way than via visual-based methods and for labeling the mammograms that are later employed to train the fully automated tool. Although most automated methods rely on supervised approaches based on a global labeling of the mammogram, the proposed method relies on pixel-level labeling, allowing better tissue classification and density measurement on a continuous scale. The fully automated method presented combines a classification scheme based on local features and thresholding operations that improve the performance of the classifier. A dataset of 655 mammograms was used to test the concordance of both approaches in measuring MD. Three expert radiologists measured MD in each of the mammograms using the semi-automated tool (DM-Scan). It was then measured by the fully automated system and the correlation between both methods was computed. The relation between MD and breast cancer was then analyzed using a case–control dataset consisting of 230 mammograms. The Intraclass Correlation Coefficient (ICC) was used to compute reliability among raters and between techniques. The results obtained showed an average ICC = 0.922 among raters when using the semi-automated tool, whilst the average correlation between the semi-automated and automated measures was ICC = 0.838. In the case–control study, the results obtained showed Odds Ratios (OR) of 1.38 and 1.50 per 10% increase in MD when using the semi-automated and fully automated approaches respectively. It can therefore be concluded that the automated and semi-automated MD assessments present a good correlation. Both the methods also found an association between MD and breast cancer risk, which warrants the proposed tools for breast cancer risk prediction and clinical decision making. A full version of the DM-Scan is freely available.     

Health-promoting effects in the gut and influence on lipid metabolism of Himanthalia elongata and Gigartina pistillata in hypercholesterolaemic Wistar rats

The intake of Himanthalia elongata and Gigartina pistillata from the Spanish Atlantic coasts was evaluated in Wistar rats. Both seaweed diets showed higher (p < 0.001) faecal excretion. Colonic fermentation increased (p < 0.001) total short-chain fatty acids (SCFAs) in Himanthalia-fed rats due to the higher (p < 0.001) levels of acetic, propionic and butyric acids. The intake of Gigartina increased (p < 0.001) propionic acid and decreased (p < 0.001) butyric acid. The apparent absorption and true retention of calcium and magnesium enhanced (p < 0.05) with Himanthalia diet, while Gigartina produced no significant effect. The serum concentration of HDL-C increased (p < 0.01), triglycerides (TGL) decreased (p < 0.001) and bile acids diminished (p < 0.001) in faeces of Himanthalia-fed rats. The Gigartina diet produced a decrease (p < 0.001) in TGL, total cholesterol (p < 0.01) and LDL-C (p < 0.05) in serum and reduced TGL in liver (p < 0.001). Thus, both seaweeds improved the lipid profile, and Himanthalia increased SCFA production and the absorption and retention of Ca and Mg as a result of the gut fermentation.     

Pea pod, broad bean pod and okara, potential sources of functional compounds

Disposal of by-products generated by plant food processing represent an important problem in the industry, but these by-products are also promising sources of compounds which may be used for their technological or nutritional properties, and today they are considered as a possible source of functional compounds. This work has contributed to the knowledge of three legume by-products, pea pod (Pisum sativum L.), broad bean pod (Vicia faba L.) and okara from soybean (Glycine max L.). These three by-products have in common that their major fraction is dietary fibre (pea pod: 58.6 g/100 g; okara: 54.3 g/100 g; broad bean pod: 40.1 g/100 g). Sucrose, glucose and fructose are the most important soluble sugars in both pods; however α-galactosides (stachyose and raffinose) are in greater concentration in okara. Protein is also a considerable component, although in higher amount in okara than in pods. Okara presents a large quantity of fat however both pods show similar low contents. Linoleic acid is the most important fatty acid; oleic acid is remarkable in okara and pea pod and linolenic acid in broad bean pod. Mineral amount is major in by-product pods than in okara, and the most important minerals are potassium, calcium and iron.