La Trobe University

About: La Trobe University is a education organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Population & Health care. The organization has 13370 authors who have published 41291 publications receiving 1138269 citations. The organization is also known as: LaTrobe University & LTU.

Genetic correlations, tradeoffs and environmental variation

Abstract: Negative genetic correlations among traits are often used as evidence for tradeoffs that can influence evolutionary trajectories in populations. While there may be evidence for negative correlations within a particular environment, genetic correlations can shift when populations encounter different environmental conditions. Here we review the evidence for these shifts by focusing on experiments that have examined genetic correlations in more than one environment. In many studies, there are significant changes in correlations and these can even switch sign across environments. This raises questions about the validity of deducing genetic constraints from studies in one environment and suggests that the interaction between environmental conditions and the expression of genetic covariation is an important avenue for future work.

Parathyroid hormone-related protein of malignancy: active synthetic fragments.

Abstract: Peptides corresponding to the amino-terminal region of the parathyroid hormone-related protein (PTHrP) of humoral hypercalcemia of malignancy were synthesized. A 34-amino acid peptide, PTHrP(1-34), was two to four times more potent than bovine or human PTH(1-34) in bioassays promoting the formation of adenosine 3',5'-monophosphate (cAMP) and plasminogen activator activity in osteogenic sarcoma cells and adenylate cyclase activity in chick kidney membranes. Like parathyroid hormone itself, in which the activity resides in the first 34 residues, PTHrP peptides of less than 30 residues from the amino terminus showed substantially reduced activity. PTHrP(1-34) had only 6% of the potency of bovine PTH(1-34) in promoting bone resorption in vitro. PTHrP(1-34) strongly promoted the excretion of cAMP and phosphorus and reduced the excretion of calcium in the isolated, perfused rat kidney consistent with the symptoms seen in malignant hypercalcemia.

Information Processing Deficits Associated with Developmental Coordination Disorder: A Meta-analysis of Research Findings

Abstract: A meta-analysis was conducted to identify information processing factors that characterise children with Developmental Coordination Disorder (DCD) A total of 50 studies yielded 374 effect sizes based on 983 DCD and 987 control children A mild generalised performance deficit was indicated, since motor-impaired children were inferior on almost all measures of information processing There were, however, several areas where their deficiencies were more pronounced The greatest deficiency was in visual-spatial processing This was evident regardless of whether or not the tasks involved a motor component Most other deficiencies were in the small-to-moderate range and included kinaesthetic and cross-modal processing The findings support the notion that perceptual problems, particularly in the visual modality, are associated with difficulties in motor coordination

Stochastic Configuration Networks: Fundamentals and Algorithms

Abstract: This paper contributes to the development of randomized methods for neural networks. The proposed learner model is generated incrementally by stochastic configuration (SC) algorithms, termed SC networks (SCNs). In contrast to the existing randomized learning algorithms for single layer feed-forward networks, we randomly assign the input weights and biases of the hidden nodes in the light of a supervisory mechanism, and the output weights are analytically evaluated in either a constructive or selective manner. As fundamentals of SCN-based data modeling techniques, we establish some theoretical results on the universal approximation property. Three versions of SC algorithms are presented for data regression and classification problems in this paper. Simulation results concerning both data regression and classification indicate some remarkable merits of our proposed SCNs in terms of less human intervention on the network size setting, the scope adaptation of random parameters, fast learning, and sound generalization.

Replication and p Intervals: p Values Predict the Future Only Vaguely, but Confidence Intervals Do Much Better:

Abstract: Replication is fundamental to science, so statistical analysis should give information about replication. Because p values dominate statistical analysis in psychology, it is important to ask what p says about replication. The answer to this question is "Surprisingly little." In one simulation of 25 repetitions of a typical experiment, p varied from .44. Remarkably, the interval-termed a p interval-is this wide however large the sample size. p is so unreliable and gives such dramatically vague information that it is a poor basis for inference. Confidence intervals, however, give much better information about replication. Researchers should minimize the role of p by using confidence intervals and model-fitting techniques and by adopting meta-analytic thinking.