Professional learning from the inside - teachers as agents of school improvement: a principal's case study

This study considered the relationship between professional learning, teacher agency and school improvement. Specifically, it explored the principal's role in supporting teacher agency in their professional learning. It found that, with appropriate pressure and support from principals, school improvement for the betterment of student learning is attainable through teacher professional learning that is based 'within' a school. Particularly, it ascertained that schools need to give greater attention to the allocation of time for teacher professional learning, specifically: time before, during and after professional learning activities. Privileging time efficiently and effectively, heightens teacher agency in their learning.

Can larger-bodied cemented femoral components reduce periprosthetic fractures? A biomechanical study

Introduction: The risk for late periprosthetic femoral fractures is higher in patients treated for a neck of femur fracture compared to osteoarthritis. It has been hypothesised that osteopenia and consequent decreased stiffness of the proximal femur are responsible for this. We investigated whether a femoral component with a bigger body would increase the torque to failure in a biaxially loaded composite Sawbone model. Material and methods: A biomechanical bone analogue was used. Two different body sizes (Exeter 44-1 vs 44-4) of a polished tapered cemented femoral stem were implanted by an experienced surgeon in 7 bone analogues each and internally rotated at 40°/s until failure. Torque to fracture and fracture energy were measured using a biaxial materials testing device (Instron 8874, MI, USA). The data were non-parametric and therefore tested with the Mann-Whitney U-test. Results: The median torque to fracture was 156.7 Nm (IQR 19.7) for the 44-1 stem and 237.1 Nm (IQR 52.9) for the 44-4 stem (p=0.001). The median fracture energy was 8.5J (IQR 7.3) for the 44-1 stem and 19.5J (IQR 8.8) for the 44-4 stem (p=0.014). Conclusions: The use of a large body polished tapered cemented stems for neck of femur fractures increases the torque to failure in a biomechanical model and therefore is likely to reduce late periprosthetic fracture risk in this vulnerable cohort.

Differences in intrinsic properties of dorsally and ventrally located lateral amygdala neurons of the rat

During Pavlovian auditory fear conditioning a previously neutral auditory stimulus (CS) gains emotional significance through pairing with a noxious unconditioned stimulus (US). These associations are believed to be formed by way of plasticity at auditory input synapses on principal neurons of the lateral nucleus of the amygdala (LA). While the LA has been implicated as a key brain structure for fear learning, how its network of cellular components performs these operations is not yet known...

Etapas del cambio en personas inactivas tras un programa de promoción de la actividad física en Atención Primaria

Objetivo El objetivo del estudio fue evaluar las Etapas del cambio en relación con la actividad física y el estado de salud general entre personas que participaron en un Programa de promoción de la actividad física (PPAF) de 12 semanas frente a un grupo control. Diseño Ensayo clínico aleatorizado. Participantes Noventa y ocho personas inactivas de ambos sexos con una edad media de 62,82 años procedentes de 2 centros de Atención Primaria del Distrito Sanitario Costa del Sol. Intervención Un PPAF organizado en grupos y siguiendo los criterios del Colegio Americano de Medicina del Deporte, 2 sesiones semanales de 60 min durante 12 semanas. Mediciones principales La variable principal de resultado fue resistencia al cambio en relación con la actividad física. La variable secundaria fue el estado de salud general (componentes físicos y mentales), determinado con el cuestionario de salud general SF12. Resultados Se encontraron diferencias significativas en las etapas del cambio a favor del grupo experimental (p < 0,05). No se encontraron diferencias estadísticamente significativas entre grupos después de la intervención en el estado general de salud. Conclusión Las etapas del cambio se modificaron en las personas inactivas que realizaron el PPAF en Atención Primaria. Futuros estudios son necesarios para identificar qué factores del entorno de los participantes influyen en la resistencia al cambio de la actividad física. Abstract Objective This study has aimed to evaluate the stages of change in relation to physical activity and overall health status among persons who participated in a 12-week Physical activity promotion program (PAPP) compared to a control group. Design Randomized clinical trial. Participants The study included 98 inactive persons of both sexes with a mean age of 62.82 years from 2 of Primary Care Centers of the Malaga Health Care District. Interventions A PAPP organized in groups according to the American College of Sports Medicine criteria including two weekly sessions of 60 minutes each for 3 months. Main measures The primary outcome was to assess resistance to change in relation to physical activity. The secondary variable was overall health (physical and mental components) determined with the SF12 general health questionnaire. Results Significant differences were found in the stages of change (P<.05). There were no significant differences found in general health status improvement in regards to the initial assessment. Conclusion The stages of change were modified in the inactive persons who carried out the PAPP in Primary Care. Future studies are needed to identify which environmental factors influence the resistance to change in physical activity of the participants.

Multivariate variance-components analysis in DTI

Twin studies are a major research direction in imaging genetics, a new field, which combines algorithms from quantitative genetics and neuroimaging to assess genetic effects on the brain. In twin imaging studies, it is common to estimate the intraclass correlation (ICC), which measures the resemblance between twin pairs for a given phenotype. In this paper, we extend the commonly used Pearson correlation to a more appropriate definition, which uses restricted maximum likelihood methods (REML). We computed proportion of phenotypic variance due to additive (A) genetic factors, common (C) and unique (E) environmental factors using a new definition of the variance components in the diffusion tensor-valued signals. We applied our analysis to a dataset of Diffusion Tensor Images (DTI) from 25 identical and 25 fraternal twin pairs. Differences between the REML and Pearson estimators were plotted for different sample sizes, showing that the REML approach avoids severe biases when samples are smaller. Measures of genetic effects were computed for scalar and multivariate diffusion tensor derived measures including the geodesic anisotropy (tGA) and the full diffusion tensors (DT), revealing voxel-wise genetic contributions to brain fiber microstructure.

Re-valuing construction materials and components through design for disassembly

The construction industry accounts for a significant portion of the material consumption of our industrialised societies. That material consumption comes at an environmental cost, and when buildings and infrastructure projects are demolished and discarded, after their useful lifespan, that environmental cost remains largely unrecovered. The expected operational lifespan of modern buildings has become disturbingly short as buildings are replaced for reasons of changing cultural expectations, style, serviceability, locational obsolescence and economic viability. The same buildings however are not always physically or structurally obsolete; the materials and components within them are very often still completely serviceable. While there is some activity in the area of recycling of selected construction materials, such as steel and concrete, this is almost always in the form of down cycling or reprocessing. Very little of this material and component resource is reuse in a way that more effectively captures its potential. One significant impediment to such reuse is that buildings are not designed in a way that facilitates easy recovery of materials and components; they are designed and built for speed of construction and quick economic returns, with little or no consideration of the longer term consequences of their physical matter. This research project explores the potential for the recovery of materials and components if buildings were designed for such future recovery; a strategy of design for disassembly. This is not a new design philosophy; design for disassembly is well understood in product design and industrial design. There are also some architectural examples of design for disassembly; however these are specialist examples and there is no significant attempt to implement the strategy in the main stream construction industry. This paper presents research into the analysis of the embodied energy in buildings, highlighting its significance in comparison with operational energy. Analysis at material, component, and whole-of-building levels shows the potential benefits of strategically designing buildings for future disassembly to recover this embodied energy. Careful consideration at the early design stage can result in the deconstruction of significant portions of buildings and the recovery of their potential through higher order reuse and upcycling.

Robust principal component analysis in water quality index development

Some statistical procedures already available in literature are employed in developing the water quality index, WQI. The nature of complexity and interdependency that occur in physical and chemical processes of water could be easier explained if statistical approaches were applied to water quality indexing. The most popular statistical method used in developing WQI is the principal component analysis (PCA). In literature, the WQI development based on the classical PCA mostly used water quality data that have been transformed and normalized. Outliers may be considered in or eliminated from the analysis. However, the classical mean and sample covariance matrix used in classical PCA methodology is not reliable if the outliers exist in the data. Since the presence of outliers may affect the computation of the principal component, robust principal component analysis, RPCA should be used. Focusing in Langat River, the RPCA-WQI was introduced for the first time in this study to re-calculate the DOE-WQI. Results show that the RPCA-WQI is capable to capture similar distribution in the existing DOE-WQI.

Combining HPLC-DAD and ICP-MS data for improved analysis of complex samples: Classification of the root samples from Cortex moutan

A combined data matrix consisting of high performance liquid chromatography–diode array detector (HPLC–DAD) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements of samples from the plant roots of the Cortex moutan (CM), produced much better classification and prediction results in comparison with those obtained from either of the individual data sets. The HPLC peaks (organic components) of the CM samples, and the ICP-MS measurements (trace metal elements) were investigated with the use of principal component analysis (PCA) and the linear discriminant analysis (LDA) methods of data analysis; essentially, qualitative results suggested that discrimination of the CM samples from three different provinces was possible with the combined matrix producing best results. Another three methods, K-nearest neighbor (KNN), back-propagation artificial neural network (BP-ANN) and least squares support vector machines (LS-SVM) were applied for the classification and prediction of the samples. Again, the combined data matrix analyzed by the KNN method produced best results (100% correct; prediction set data). Additionally, multiple linear regression (MLR) was utilized to explore any relationship between the organic constituents and the metal elements of the CM samples; the extracted linear regression equations showed that the essential metals as well as some metallic pollutants were related to the organic compounds on the basis of their concentrations

Errors in the knee joint forces and moments during gait depending on the foot and knee prosthetic components

Background Previously studies showed that inverse dynamics based on motion analysis and force-plate is inaccurate compared to direct measurements for individuals with transfemoral amputation (TFA). Indeed, direct measurements can appropriately take into account the absorption at the prosthetic foot and the resistance at the prosthetic knee. [1-3] However, these studies involved only a passive prosthetic knee. Aim The objective of the present study was to investigate if different types of prosthetic feet and knees can exhibit different levels of error in the knee joint forces and moments. Method Three trials of walking at self-selected speed were analysed for 9 TFAs (7 males and 2 females, 47±9 years old, 1.76±0.1 m 79±17 kg) with a motion analysis system (Qualisys, Goteborg, Sweden), force plates (Kitsler, Winterthur, Switzerland) and a multi-axial transducer (JR3, Woodland, USA) mounted above the prosthetic knee [1-17]. TFAs were all fitted with an osseointegrated implant system. The prostheses included different type of foot (N=5) and knee (N=3) components. The root mean square errors (RMSE) between direct measurements and the knee joint forces and moments estimated by inverse dynamics were computed for stance and swing phases of gait and expressed as a percentage of the measured amplitudes. A one-way Kruskal-Wallis ANOVA was performed (Statgraphics, Levallois-Perret, France) to analyse the effects of the prosthetic components on the RMSEs. Cross-effects and post-hoc tests were not analysed in this study. Results A significant effect (*) was found for the type of prosthetic foot on anterior-posterior force during swing (p=0.016), lateral-medial force during stance (p=0.009), adduction-abduction moment during stance (p=0.038), internal-external rotation moment during stance (p=0.014) and during swing (p=0.006), and flexion-extension moment during stance (p = 0.035). A significant effect (#) was found for the type of prosthetic knee on anterior-posterior force during swing (p=0.018) and adduction-abduction moment during stance (p=0.035). Discussion & Conclusion The RMSEs were larger during swing than during stance. It is because the errors on accelerations (as derived from motion analysis) become substantial with respect to the external loads. Thus, inverse dynamics during swing should be analysed with caution because the mean RMSEs are close to 50%. Conversely, there were fewer effects of the prosthetic components on RMSE during swing than during stance and, accordingly, fewer effects due to knees than feet. Thus, inverse dynamics during stance should be used with caution for comparison of different prosthetic components.

Condition monitoring and rating of bridge components in a rail or road network by using SHM systems within SRP

The safety and performance of bridges could be monitored and evaluated by Structural Health Monitoring (SHM) systems. These systems try to identify and locate the damages in a structure and estimate their severities. Current SHM systems are applied to a single bridge, and they have not been used to monitor the structural condition of a network of bridges. This paper propose a new method which will be used in Synthetic Rating Procedures (SRP) developed by the authors of this paper and utilizes SHM systems for monitoring and evaluating the condition of a network of bridges. Synthetic rating procedures are used to assess the condition of a network of bridges and identify their ratings. As an additional part of the SRP, the method proposed in this paper can continuously monitor the behaviour of a network of bridges and therefore it can assist to prevent the sudden collapses of bridges or the disruptions to their serviceability. The method could be an important part of a bridge management system (BMS) for managers and engineers who work on condition assessment of a network of bridges.

Body composition and components of energy expenditure in children with end-stage liver disease

Background: Better understanding of body composition and energy metabolism in pediatric liver disease may provide a scientific basis for improved medical therapy aimed at achieving optimal nutrition, slowing progression to end-stage liver disease (ESLD), and improving the outcome of liver transplantation. Methods: Twenty-one children less than 2 years of age with ESLD awaiting liver transplantation and 15 healthy, aged-matched controls had body compartment analysis using a four compartment model (body cell mass, fat mass, extracellular water, and extracellular solids). Subjects also had measurements of resting energy expenditure (REE) and respiratory quotient (RQ) by indirect calorimetry. Nine patients and 15 control subjects also had measurements of total energy expenditure (TEE) using doubly labelled water. Results: Mean weights and heights were similar in the two groups. Compared with control subjects, children with ESLD had higher relative mean body cell mass (33 ± 2% vs 29 ± 1% of body weight, P < 0.05), but had similar fat mass, extracellular water, and extracellular solid compartments (18% vs 20%, 41% vs 38%, and 7% vs 13% of body weight respectively). Compared with control subjects, children with ESLD had 27% higher mean REE/body weight (0.285 ± 0.013 vs 0.218. ± 0.013 mJ/kg/24h, P < 0.001), 16% higher REE/unit cell mass (P < 0.05); and lower mean RQ (P < 0.05). Mean TEE of patients was 4.70 ± 0.49 mJ/24h vs 3.19 ± 0.76 in controls, (P < 0.01). Conclusions: In children, ESLD is a hypermetabolic state adversely affecting the relationship between metabolic and non-metabolic body compartments. There is increased metabolic activity within the body cell mass with excess lipid oxidation during fasting and at rest. These findings have implications for the design of appropriate nutritional therapy.

Food literacy: Definitions, components, learning and links to diet and health outcomes

Recently, the term ‘food literacy’ has emerged in policy, research and practice to describe the collection of knowledge, skills and behaviours required to practically meet food needs. This presentation will described research undertaken to empirically define the term and propose its impact on nutrition

Overfitting Bayesian mixture models with an unknown number of components

This paper proposes solutions to three issues pertaining to the estimation of finite mixture models with an unknown number of components: the non-identifiability induced by overfitting the number of components, the mixing limitations of standard Markov Chain Monte Carlo (MCMC) sampling techniques, and the related label switching problem. An overfitting approach is used to estimate the number of components in a finite mixture model via a Zmix algorithm. Zmix provides a bridge between multidimensional samplers and test based estimation methods, whereby priors are chosen to encourage extra groups to have weights approaching zero. MCMC sampling is made possible by the implementation of prior parallel tempering, an extension of parallel tempering. Zmix can accurately estimate the number of components, posterior parameter estimates and allocation probabilities given a sufficiently large sample size. The results will reflect uncertainty in the final model and will report the range of possible candidate models and their respective estimated probabilities from a single run. Label switching is resolved with a computationally light-weight method, Zswitch, developed for overfitted mixtures by exploiting the intuitiveness of allocation-based relabelling algorithms and the precision of label-invariant loss functions. Four simulation studies are included to illustrate Zmix and Zswitch, as well as three case studies from the literature. All methods are available as part of the R package Zmix, which can currently be applied to univariate Gaussian mixture models.

A Phenomic Scan of the Norfolk Island Genetic Isolate Identifies a Major Pleiotropic Effect Locus Associated with Metabolic and Renal Disorder Markers

Multiphenotype genome-wide association studies (GWAS) may reveal pleiotropic genes, which would remain undetected using single phenotype analyses. Analysis of large pedigrees offers the added advantage of more accurately assessing trait heritability, which can help prioritise genetically influenced phenotypes for GWAS analysis. In this study we performed a principal component analysis (PCA), heritability (h2) estimation and pedigree-based GWAS of 37 cardiovascular disease -related phenotypes in 330 related individuals forming a large pedigree from the Norfolk Island genetic isolate. PCA revealed 13 components explaining >75% of the total variance. Nine components yielded statistically significant h2 values ranging from 0.22 to 0.54 (P<0.05). The most heritable component was loaded with 7 phenotypic measures reflecting metabolic and renal dysfunction. A GWAS of this composite phenotype revealed statistically significant associations for 3 adjacent SNPs on chromosome 1p22.2 (P<1x10-8). These SNPs form a 42kb haplotype block and explain 11% of the genetic variance for this renal function phenotype. Replication analysis of the tagging SNP (rs1396315) in an independent US cohort supports the association (P = 0.000011). Blood transcript analysis showed 35 genes were associated with rs1396315 (P<0.05). Gene set enrichment analysis of these genes revealed the most enriched pathway was purine metabolism (P = 0.0015). Overall, our findings provide convincing evidence for a major pleiotropic effect locus on chromosome 1p22.2 influencing risk of renal dysfunction via purine metabolism pathways in the Norfolk Island population. Further studies are now warranted to interrogate the functional relevance of this locus in terms of renal pathology and cardiovascular disease risk.