A restricted curriculum for second language learners : a self-fulfilling teacher strategy?

The focus of this article is on relations between classroom interaction, curricular knowledge and student engagement in diverse classrooms. It is based on a study with ethnographic perspective in which two primary school classes in Sweden were followed for three years. The analysis draws on Halliday's Systemic Functional Linguistics. The results indicate that language use in the classrooms is on a basic everyday level and that high teacher control results in low-demanding tasks and low engagement among students. Interaction in the classrooms mainly consists of short talk-turns with fragmented language, frequent repairs and interruptions, while writing and reading consists of single words and short sentences. Although the classroom atmosphere is friendly and inclusive, second language students are denied necessary opportunities to develop curricular knowledge and Swedish at the advanced level, which they will need higher up in the school system. The restricted curriculum that these students are offered in school thus restricts their opportunities to school success. Thus, I argue for a more reflective and critical approach regarding language use in classrooms.

Gender differences in adherence to sodium-restricted diet patients with heart failure.

Background

Despite the importance of the sodium-restricted diet (SRD) to heart failure (HF) management, patient adherence is poor. Little is known about gender differences in adherence or factors that affect patients' ability to follow SRD recommendations. The purposes of this study were to determine whether there were gender differences in (1) adherence to the SRD; (2) knowledge about SRD and HF self-care; and (3) perceived barriers to following the SRD.
Methods and Results

Forty-one men and 27 women completed the Heart Failure Attitudes and Barriers questionnaire that measured HF self-care, knowledge, and perceived barriers to follow an SRD. Diet adherence was measured by 24-hour urinary sodium excretion (UNa). Women were more adherent to the SRD than men as reflected by 24-hour urine excretion (2713 versus 3859 mg UNa, P = .01). Women recognized signs of excess sodium intake such as fluid buildup (P = .001) and edema (P = .01) more often than men and had better understanding of appropriate actions to take related to following an SRD. There were no gender differences in perceived barriers to follow an SRD.
Conclusions

Although men and women perceived similar barriers, women were more adherent to the SRD and had greater knowledge about following an SRD. Further investigation of this phenomenon is warranted to determine if better adherence contributes to improved outcomes in women.

Lupin (Lupinus albus) protein isolate (L-ISO) has adequate nutritional value and reduces large intestinal weight in rats after restricted and ad libitum feeding.

Background: A protein isolate from white lupin (Lupinus albus; L-ISO) has potential as a novel human food ingredient, but its nutritional effects are unknown.

Methods: We evaluated protein quality and effects on body composition in rats of isoenergic diets of L-ISO, lactalbumin, or casein with both restricted (10-day) and ad libitum (28-day)intake. The diets were equivalent in protein per se, but supplementation was used to balance essential amino acid levels.

Results: In both studies, the rats consumed similar amounts of each diet, and no effect of diet on the gain:feed ratio was observed--though gain:N ratio and net protein utilization were slightly lower for the L-ISO diet. Lower large intestinal weights after the L-ISO than after the lactalbumin diet were observed in both studies. The L-ISO diet resulted in lowered body fat percentage in the 10-day study but in an elevated level in the 28-day study. Liver composition (DNA, RNA, glycogen, and fat) and plasma levels of some amino acids (His, Thr, Ala, Pro, Tyr, Val and Met) were affected by diet, but no effects on plasma lipid, glucose, or uric acid were observed.

Conclusion: The L-ISO diet did not affect feed intake and has adequate nutritional quality in rats whilst modifying large intestinal weight in a potentially beneficial manner--suggesting potential for this protein in human nutrition.

CD1d-restricted NKT cells contribute to malarial splenomegaly and enhance parasite-specific antibody responses

CD1d-restricted NKT cells are a novel T cell lineage with unusual features. They co-express some NK cell receptors and recognize glycolipid antigens through an invariant T cell receptor (TCR) in the context of CD1d molecules. Upon activation through the TCR, NKT cells produce large amounts of IFN- and IL-4. It has been proposed that rapid cytokine output by activated NKT cells may induce bystander activation of other lymphoid lineages. The impact of CD1d-restricted NKT cell activation in the induction of B cell-mediated immune responses to infection is still unclear. We show here that CD1-restricted NKT cells contribute to malarial splenomegaly associated with expansion of the splenic B cell pool and enhance parasite-specific antibody formation in response to Plasmodium berghei infection. The increased B cell-mediated response correlates with the ability of NKT cells to promote Th2 immune responses. Additionally, antibody responses against the glycosylphosphatidylinositol (GPI)-anchored protein merozoite surface protein 1 (MSP-1) were found to be significantly lower in CD1-/- mice compared to wild-type animals. P. berghei-infected MHC class II (MHCII)-/- mice also generated antibodies against MSP-1, suggesting that antibody production against GPI-anchored antigens in response to malaria infection can arisefrom both MHCII-dependent and independent pathways.

Pervasive limitations : innovating with ambient intelligence (AmI) technologies and restricted absorptive capacity in Australian SME manufacturers

The last 25 years have seen rapid increases in the number and sophistication of technological and process innovations in large manufacturers, producing dramatic improvements in productivity and efficiency. However, smaller manufacturers’ adoption of such innovations has been uneven. Ambient Intelligence (AmI) technologies are being positioned as the next performance and productivity enhancing purchase for manufacturers. This paper defines and gives examples of AmI technologies in current use, summarises AmI technologies of potential interest to small and medium enterprise (SME) manufacturers, and identifies potential impacts of restricted absorptive capacity in SMEs on the adoption of AmI technologies. Comparing two SME manufacturers, one from Germany and one from Australia illustrates a potential application of generic AmI technology based business solutions to a range of SME manufacturers.

Restricted dissimilarity functions and penalty functions

In this work we introduce the definition of restricted dissimilarity functions and we link it with some other notions, such as metrics. In particular, we also show how restricted dissimilarity functions can be used to build penalty functions.

The restricted seed rain of a mistletoe specialist

Specialist frugivores are the dominant consumers of mistletoe fruit in many regions and have been shown to intensify infections of host plants as a result of their rapid gut passage rates and dependence on existing infections. The role of specialist frugivores in long distance dispersal of mistletoe and establishment of new infections is unclear, and has not been explicitly evaluated previously. Here we critically examine the premise that specialists are the dominant dispersers by examining the role of an Australian mistletoe specialist (mistletoebird Dicaeum hirundinaceum Dicaeidae) in dispersing mistletoe (Amyema preissii Santalales: Loranthaceae) seeds beyond infected host stands. We use two primary lines of evidence - presence of birds using remote call recorders, and presence of dispersed seeds via surveys for defecated seeds on host branches. The observed and inferred movements of the mistletoebird were wholly restricted to habitat patches containing mistletoe, and this bird was not observed to transport seeds to nearby uninfected host stands within the study system. While mistletoe specialists may provide much of the within-stand dispersal service for mistletoes, this serves only to aggregate and intensify existing infections. We suggest that long distance dispersal of mistletoe seeds beyond existing hosts and infection centres is not performed by these dietary specialists, these services more likely to be provided by generalist frugivores and other occasional mistletoe fruit consumers.

Mixed-variate restricted Boltzmann machines

Modern datasets are becoming heterogeneous. To this end, we present in this paper Mixed- Variate Restricted Boltzmann Machines for simultaneously modelling variables of multiple types and modalities, including binary and continuous responses, categorical options, multicategorical choices, ordinal assessment and category-ranked preferences. Dependency among variables is modeled using latent binary variables, each of which can be interpreted as a particular hidden aspect of the data. The proposed model, similar to the standard RBMs, allows fast evaluation of the posterior for the latent variables. Hence, it is naturally suitable for many common tasks including, but not limited to, (a) as a pre-processing step to convert complex input data into a more convenient vectorial representation through the latent posteriors, thereby oering a dimensionality reduction capacity, (b) as a classier supporting binary, multiclass, multilabel, and label-ranking outputs, or a regression tool for continuous outputs and (c) as a data completion tool for multimodal and heterogeneous data. We evaluate the proposed model on a large-scale dataset using the world opinion survey results on three tasks: feature extraction and visualization, data completion and prediction.

Embedded restricted Boltzmann machines for fusion of mixed data types and applications in social measurements analysis

Analysis and fusion of social measurements is important to understand what shapes the public’s opinion and the sustainability of the global development. However, modeling data collected from social responses is challenging as the data is typically complex and heterogeneous, which might take the form of stated facts, subjective assessment, choices, preferences or any combination thereof. Model-wise, these responses are a mixture of data types including binary, categorical, multicategorical, continuous, ordinal, count and rank data. The challenge is therefore to effectively handle mixed data in the a unified fusion framework in order to perform inference and analysis. To that end, this paper introduces eRBM (Embedded Restricted Boltzmann Machine) – a probabilistic latent variable model that can represent mixed data using a layer of hidden variables transparent across different types of data. The proposed model can comfortably support largescale data analysis tasks, including distribution modelling, data completion, prediction and visualisation. We demonstrate these versatile features on several moderate and large-scale publicly available social survey datasets.

Cumulative restricted Boltzmann machines for ordinal matrix data analysis

Ordinal data is omnipresent in almost all multiuser-generated feedback - questionnaires, preferences etc. This paper investigates modelling of ordinal data with Gaussian restricted Boltzmann machines (RBMs). In particular, we present the model architecture, learning and inference procedures for both vector-variate and matrix-variate ordinal data. We show that our model is able to capture latent opinion profile of citizens around the world, and is competitive against state-of-art collaborative filtering techniques on large-scale public datasets. The model thus has the potential to extend application of RBMs to diverse domains such as recommendation systems, product reviews and expert assessments.

A slice sampler for restricted hierarchical beta process with applications to shared subspace learning

Hierarchical beta process has found interesting applications in recent years. In this paper we present a modified hierarchical beta process prior with applications to hierarchical modeling of multiple data sources. The novel use of the prior over a hierarchical factor model allows factors to be shared across different sources. We derive a slice sampler for this model, enabling tractable inference even when the likelihood and the prior over parameters are non-conjugate. This allows the application of the model in much wider contexts without restrictions. We present two different data generative models – a linear Gaussian-Gaussian model for real valued data and a linear Poisson-gamma model for count data. Encouraging transfer learning results are shown for two real world applications – text modeling and content based image retrieval.