Collaborative Writing and Revising: with whom and how?:An experimental study into the interaction between group composition and method of instruction when revising collaboratively in a foreing language in higher education

Wie een vorm van samenwerkend leren in de schrijflessen wil integreren, staat voor de vraag hoe de leerlingen het best te groeperen: welke groepssamenstelling van minder goede en goede reviseerders en schrijvers is de beste? Elke Van Steendam, Gert Rijlaarsdam, Huub van den Bergh en Lies Sercu onderzochten die vraag in twee instructiecondities. De resultaten wijzen uit dat in een meer traditionele leren-door-oefenen conditie zwakkere studenten de meeste leerwinst boeken in een heterogene groepssamenstelling, terwijl de betere studenten het meeste baat hebben bij een homogeen revisiegroepje. In de leren-door-observeren conditie maakt de groepssamenstelling niet uit

Kultuurstereotipering in Nederlandse moedertaal-taalhandboeke

Based on the assumption that textbooks serve as a mirror of the social and political order, the purpose of this article is to provide insight into the role of textbooks in the maintenance and legitimization of ethnic power relations. This qualitative study investigates visual representations in Dutch mother tongue language textbooks. A Critical Discourse Analysis (CDA) supported by a thematic analysis evaluate the visual material of one popular Dutch textbook series in terms of cultural stereotyping of the “other”. The conceptual framework comprises an explication of the concepts and theories on attitude, culture and visual studies. Influential issues on Dutch textbook representation are described in the literature study. The findings show that the rethoric confirming the “other”ness of the “other” in Dutch textbooks, has not changed much since the research of Teun van Dijk in 1987. The visual material in the Dutch data is polarised by the model example of the dominant white group on the one hand and the problematic, poor and primitive of the non-Western world on the other hand. The findings are presented as themes from the thematic analysis.gv201

Molecular and neurological characterizations of three Saudi families with lipoid proteinosis

<p>Abstract</p> <p>Background</p> <p>Lipoid proteinosis is a rare autosomal recessive disease characterized by cutaneous and mucosal lesions and hoarseness appearing in early childhood. It is caused by homozygous or compound heterozygous mutations in the <it>ECM1 </it>gene. The disease is largely uncharacterized in Arab population and the mutation(s) spectrum in the Arab population is largely unknown. We report the neurologic and neuroradiologic characteristics and <it>ECM1 </it>gene mutations of seven individuals with lipoid proteinosis (LP) from three unrelated consanguineous families.</p> <p>Methods</p> <p>Clinical, neurologic, and neuro-ophthalmologic examinations; skin histopathology; brain CT and MRI; and sequencing of the full<it>ECM1 </it>gene.</p> <p>Results</p> <p>All seven affected individuals had skin scarring and hoarseness from early childhood. The two children in Family 1 had worse skin involvement and worse hoarseness than affected children of Families 2 and 3. Both children in Family 1 were modestly mentally retarded, and one had typical calcifications of the amygdalae on CT scan. Affected individuals in Families 2 and 3 had no grossneurologic, neurodevelopmental, or neuroimaging abnormalities. Skin histopathology was compatible with LP in all three families. Sequencing the full coding region of <it>ECM1 </it>gene revealed two novel mutationsin Family 1 (c.1300-1301delAA) and Family 2 (p.Cys269Tyr) and in Family 3 a previously described 1163 bp deletion starting 34 bp into intron 8.</p> <p>Conclusions</p> <p>These individuals illustrate the neurologic spectrum of LP, including variable mental retardation, personality changes, and mesial temporal calcificationand imply that significant neurologic involvement may be somewhat less common than previously thought. The cause of neurologic abnormalities was not clear from either neuroimaging or from what is known about <it>ECM1 </it>function. The severity of dermatologic abnormalities and hoarseness generally correlated with neurologic abnormalities, with Family 1 being somewhat more affected in all spheres than the other two families. Nevertheless, phenotype-genotype correlation was not obvious, possibly because of difficulty quantifying the neurologic phenotype and because of genetic complexity.</p

The functional role of temperate forest understorey vegetation in a changing world

Temperate forests cover 16% of the global forest area. Within these forests, the understorey is an important biodiversity reservoir that can influence ecosystem processes and functions in multiple ways. However, we still lack a thorough understanding of the relative importance of the understorey for temperate forest functioning. As a result, understoreys are often ignored during assessments of forest functioning and changes thereof under global change. We here compiled studies that quantify the relative importance of the understorey for temperate forest functioning, focussing on litter production, nutrient cycling, evapotranspiration, tree regeneration, pollination and pathogen dynamics. We describe the mechanisms driving understorey functioning and develop a conceptual framework synthesizing possible effects of multiple global change drivers on understorey-mediated forest ecosystem functioning. Our review illustrates that the understorey's contribution to temperate forest functioning is significant but varies depending on the ecosystem function and the environmental context, and more importantly, the characteristics of the overstorey. To predict changes in understorey functioning and its relative importance for temperate forest functioning under global change, we argue that a simultaneous investigation of both overstorey and understorey functional responses to global change will be crucial. Our review shows that such studies are still very scarce, only available for a limited set of ecosystem functions and limited to quantification, providing little data to forecast functional responses to global change

The Spot-Forward Exchange Rate Relation in Indian Foreign Exchange Market An Analysis

Forward exchange rate bias explanation generally falls into two categories – assumption of rational expectation resulting in a risk premium and expectation errors which is systematic. The paper tests the bias in the Indian forward exchange markets using one-month and three month forward contracts. The study finds that the three month contracts have larger prediction errors than the one-month contracts. The also paper finds that the prediction errors have information content which leads to assume the presence of risk premium. The study also finds that risk one-month contracts have lesser variability vis-à-vis the three month contracts

Characterization of Coastal Urban Watershed Bacterial Communities Leads to Alternative Community-Based Indicators

BACKGROUND: Microbial communities in aquatic environments are spatially and temporally dynamic due to environmental fluctuations and varied external input sources. A large percentage of the urban watersheds in the United States are affected by fecal pollution, including human pathogens, thus warranting comprehensive monitoring. METHODOLOGY/PRINCIPAL FINDINGS: Using a high-density microarray (PhyloChip), we examined water column bacterial community DNA extracted from two connecting urban watersheds, elucidating variable and stable bacterial subpopulations over a 3-day period and community composition profiles that were distinct to fecal and non-fecal sources. Two approaches were used for indication of fecal influence. The first approach utilized similarity of 503 operational taxonomic units (OTUs) common to all fecal samples analyzed in this study with the watershed samples as an index of fecal pollution. A majority of the 503 OTUs were found in the phyla Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. The second approach incorporated relative richness of 4 bacterial classes (Bacilli, Bacteroidetes, Clostridia and alpha-proteobacteria) found to have the highest variance in fecal and non-fecal samples. The ratio of these 4 classes (BBC:A) from the watershed samples demonstrated a trend where bacterial communities from gut and sewage sources had higher ratios than from sources not impacted by fecal material. This trend was also observed in the 124 bacterial communities from previously published and unpublished sequencing or PhyloChip- analyzed studies. CONCLUSIONS/SIGNIFICANCE: This study provided a detailed characterization of bacterial community variability during dry weather across a 3-day period in two urban watersheds. The comparative analysis of watershed community composition resulted in alternative community-based indicators that could be useful for assessing ecosystem health

Exploring spatial-frequency-sequential relationships for motor imagery classification with recurrent neural network

Abstract Background Conventional methods of motor imagery brain computer interfaces (MI-BCIs) suffer from the limited number of samples and simplified features, so as to produce poor performances with spatial-frequency features and shallow classifiers. Methods Alternatively, this paper applies a deep recurrent neural network (RNN) with a sliding window cropping strategy (SWCS) to signal classification of MI-BCIs. The spatial-frequency features are first extracted by the filter bank common spatial pattern (FB-CSP) algorithm, and such features are cropped by the SWCS into time slices. By extracting spatial-frequency-sequential relationships, the cropped time slices are then fed into RNN for classification. In order to overcome the memory distractions, the commonly used gated recurrent unit (GRU) and long-short term memory (LSTM) unit are applied to the RNN architecture, and experimental results are used to determine which unit is more suitable for processing EEG signals. Results Experimental results on common BCI benchmark datasets show that the spatial-frequency-sequential relationships outperform all other competing spatial-frequency methods. In particular, the proposed GRU-RNN architecture achieves the lowest misclassification rates on all BCI benchmark datasets. Conclusion By introducing spatial-frequency-sequential relationships with cropping time slice samples, the proposed method gives a novel way to construct and model high accuracy and robustness MI-BCIs based on limited trials of EEG signals