Variability of nanoindentation responses of bone and artificial bone-like composites

Nanoindentation is a popular technique for measuring the intrinsic mechanical response of bone and has been used to measure a single-valued elastic modulus. However, bone is a composite material with 20-80 nm hydroxyapatite plates embedded in a collagen matrix, and modern instrumentation allows for measurements at these small length scales. The present study examines the indentation response of bone and artificial gelatin-apatite nanocomposite materials across three orders of magnitude of lengthscale, from nanometers to micrometers, to isolate the composite phase contributions to the overall response. The load-displacement responses were variable and deviated from the quadratic response of homogeneous materials at small depths. The distribution of apparent elastic modulus values narrowed substantially with increasing indentation load. Indentation of particulate nanocomposites was simulated using finite element analysis. Modeling results replicated the convergence in effective modulus seen in the experiments. It appears that the apatite particles are acting as the continuous ("matrix") phase in bone and nanocomposites. Copyright © 2004 by ASME.

MicroRNA regulation and the variability of human cortical gene expression

Understanding the driving forces of gene expression variation within human populations will provide important insights into the molecular basis of human phenotypic variation. In the genome, the gene expression variability differs among genes, and at prese

Long-term changes and variability of monthly extreme temperatures in India

Extreme temperatures are changing worldwide together with changes in the mean temperatures. This study investigates the long-term trends and variations of the monthly maximum and minimum temperatures and their effects on seasonal fluctuations in various climatological regions in India. The magnitude of the trends and their statistical significance were determined by parametric ordinary least square regression techniques and the variations were determined by the respective coefficient of variations. The results showed that the monthly maximum temperature increased, though unevenly, over the last century. Minimum temperature changes were more variable than maximum temperature changes, both temporally and spatially, with results of lesser significance. The results of this study are good indicators of Indian climate variability and its changes over the last century. © Springer-Verlag 2009.

Assessing seasonal precipitation trends in India using parametric and non-parametric statistical techniques

This paper provides an insight into the long-term trends of the four seasonal and annual precipitations in various climatological regions and sub-regions in India. The trends were useful to investigate whether Indian seasonal rainfall is changing in terms of magnitude or location-wise. Trends were assessed over the period of 1954-2003 using parametric ordinary least square fits and non-parametric Mann-Kendall technique. The trend significance was tested at the 95% confidence level. Apart from the trends for individual climatological regions in India and the average for the whole of India, trends were also specifically determined for the possible smaller geographical areas in order to understand how different the trends would be from the bigger spatial scales. The smaller geographical regions consist of the whole southwestern continental state of Kerala. It was shown that there are decreasing trends in the spring and monsoon rainfall and increasing trends in the autumn and winter rainfalls. These changes are not always homogeneous over various regions, even in the very short scales implying a careful regional analysis would be necessary for drawing conclusions regarding agro-ecological or other local projects requiring change in rainfall information. Furthermore, the differences between the trend magnitudes and directions from the two different methods are significantly small and fall well within the significance limit for all the cases investigated in Indian regions (except where noted). © 2010 Springer-Verlag.

Microbial carbonate precipitation: Correlation of S-wave velocity with calcite precipitation

The use of microbial induced precipitation as a soil improvement technique has been growing in geotechnical domains where ureolytic bacteria that raise the pH of the system and induce calcium carbonate (CaCO3) precipitation are used. For many applications, it is useful to assess the degree of CaCO 3 precipitation by non-destructive testing. This study investigates the feasibility of S-wave velocity measurements to evaluate the amount of calcite precipitation by laboratory testing. Two sets of cemented specimen were tested. The first were samples terminated at different stages of cementation. The second were samples that went through different chemical treatments. These variations were made to find out if these factors would affect the S-wave velocity- cementation relationship. If chemical reaction efficiency was assumed to be constant throughout each test, the relationship between S-wave velocity (Vs) and the amount of CaCO3 precipitation was found to be approximately linear. This correlation between S-wave velocity and calcium carbonate precipitation validates its use as an indicator of the amount of calcite precipitation © 2011 ASCE.

Bayesian classification of acoustical waveforms under environmental variability

We present in this paper a new multivariate probabilistic approach to Acoustic Pulse Recognition (APR) for tangible interface applications. This model uses Principle Component Analysis (PCA) in a probabilistic framework to classify tapping pulses with a high degree of variability. It was found that this model, achieves a higher robustness to pulse variability than simpler template matching methods, specifically when allowed to train on data containing high variability. © 2011 IEEE.

Probabilistic computation in human perception under variability in encoding precision.

A key function of the brain is to interpret noisy sensory information. To do so optimally, observers must, in many tasks, take into account knowledge of the precision with which stimuli are encoded. In an orientation change detection task, we find that encoding precision does not only depend on an experimentally controlled reliability parameter (shape), but also exhibits additional variability. In spite of variability in precision, human subjects seem to take into account precision near-optimally on a trial-to-trial and item-to-item basis. Our results offer a new conceptualization of the encoding of sensory information and highlight the brain's remarkable ability to incorporate knowledge of uncertainty during complex perceptual decision-making.

Variability in encoding precision accounts for visual short-term memory limitations.

It is commonly believed that visual short-term memory (VSTM) consists of a fixed number of "slots" in which items can be stored. An alternative theory in which memory resource is a continuous quantity distributed over all items seems to be refuted by the appearance of guessing in human responses. Here, we introduce a model in which resource is not only continuous but also variable across items and trials, causing random fluctuations in encoding precision. We tested this model against previous models using two VSTM paradigms and two feature dimensions. Our model accurately accounts for all aspects of the data, including apparent guessing, and outperforms slot models in formal model comparison. At the neural level, variability in precision might correspond to variability in neural population gain and doubly stochastic stimulus representation. Our results suggest that VSTM resource is continuous and variable rather than discrete and fixed and might explain why subjective experience of VSTM is not all or none.

Morphological variability between wild populations and inbred stocks of a Chinese minnow, Gobiocypris rarus

Gobiocypris rarus, a small, native cyprinid fish, is currently widely used in research on fish pathology, genetics, toxicology, embryology, and physiology in China. To develop this species as a model laboratory animal, inbred strains have been successfully created. In this study, to explore a method to discriminate inbred strains and evaluate inbreeding effects, morphological variation among three wild populations and three inbred stocks of G. rarus was investigated by the multivariate analysis of eight meristic and 30 morphometric characters. Tiny intraspecific variations in meristic characters were found, but these were not effective for population distinction. Stepwise discriminant analysis and cluster analysis of conventional measures and truss network data showed considerabe divergence among populations, especially between wild populations and inbred stocks. The average discriminant accuracy for all populations was 82.1% based on conventional measures and 86.4% based on truss data, whereas the discriminant accuracy for inbred strains was much higher. These results suggested that multivariate analyses of morphometric characters are an effective method for discriminating inbred strains of G. rarus. Morphological differences between wild populations and inbred strains appear to result from both genetic differences and environmental factors. Thirteen characters, extracted from stepwise discriminant analysis, played important roles in morphological differentiation. These characters were mainly measures related to body depth and head size.

High variability of the gvpA-gvpC region in Microcystis

Gas vesicles provide buoyancy to Microcystis and other common cyanobacterial bloom-forming species. gvpA and gvpC are structural genes encoding gas vesicle proteins. Phylogenetic analyses of 10 Microcystis strains/uncultured samples showed that gvpC and each intergenic segment of the gvpA-gvpC region can be divided into two types. The combination of different types of gvpC and intergenic segments is an important factor that diversifies this genomic region. Some Microcystis strains isolated in China possess a 172 to 176 bp sequence tag in the intergenic segment between gvpA and gvpC. The gvpA-gvpC region in Microcystis can be divided into at least 4 classes and more numbers of subclasses. Compared to rbcLX and other regions, the high variability of the gvpA-gvpC region should be more useful in identifying geographical isolates or ecotypes of Microcystis.

Microsatellites assessment of Chinese sturgeon (Acipenser sinensis Gray) genetic variability

Four microsatellites were used to examine the genetic variability of the spawning stocks of Chinese sturgeon, Acipenser sinensis, from the Yangtze River sampled over a 3-year period (1999-2001). Within 60 individuals, a total of 28 alleles were detected over four polymorphic microsatellite loci. The number of alleles per locus ranged from 4 to 15, with an average allele number of 7. The number of genotypes per locus ranged from 6 to 41. The genetic diversity of four microsatellite loci varied from 0.34 to 0.67, with an average value of 0.54. For the four microsatellite loci, the deviation from the Hardy-Weinberg equilibrium was mainly due to null alleles. The mean number of alleles per locus and the mean heterozygosity were lower than the average values known for anadromous fishes. Fish were clustered according to their microsatellite characteristics using an unsupervised 'Artificial Neural Networks' method entitled 'Self-organizing Map'. The results revealed no significant genetic differentiation considering genetic distance among samples collected during different years. Lack of heterogeneity among different annual groups of spawning stocks was explained by the complex age structure (from 8 to 27 years for males and 12 to 35 years for females) of Chinese sturgeon, leading to formulate an hypothesis about the maintenance of genetic diversity and stability in long-lived animals.