An improved modal strain energy method for damage assessment

The modal strain energy method, which depends on the vibration characteristics of the structure, has been reasonably successful in identifying and localising damage in the structure. However, existing strain energy methods require the first few modes to be measured to provide meaningful damage detection. Use of individual modes with existing strain energy methods may indicate false alarms or may not detect the damage at or near the nodal points. This paper proposes a new modal strain energy based damage index which can detect and localize the damage using any one of the modes measured and illustrates its application for beam structures. It becomes evident that the proposed strain energy based damage index also has potential for damage quantification.

Carbon pools and fluxes along an environmental gradient in northern Arizona

Carbon pools and fluxes were quantified along an environmental gradient in northern Arizona. Data are presented on vegetation, litter, and soil C pools and soil CO2 fluxes from ecosystems ranging from shrub-steppe through woodlands to coniferous forest and the ecotones in between. Carbon pool sizes and fluxes in these semiarid ecosystems vary with temperature and precipitation and are strongly influenced by canopy cover. Ecosystem respiration is approximately 50 percent greater in the more mesic, forest environment than in the dry shrub-steppe environment. Soil respiration rates within a site vary seasonally with temperature but appear to be constrained by low soil moisture during dry summer months, when approximately 75% of total annual soil respiration occurs. Total annual amount of CO2 respired across all sites is positively correlated with annual precipitation and negatively correlated with temperature. Results suggest that changes in the amount and periodicity of precipitation will have a greater effect on C pools and fluxes than will changes in temperature :in the semiarid Southwestern United States.

Implications of patterns of carbon pools and fluxes across a semiarid environmental gradient

Landscape scale environmental gradients present variable spatial patterns and ecological processes caused by climate, topography and soil characteristics and, as such, offer candidate sites to study environmental change. Data are presented on the spatial pattern of dominant species, biomass, and carbon pools and the temporal pattern of fluxes across a transitional zone shifting from Great Basin Desert scrub, up through pinyon-juniper woodlands and into ponderosa pine forest and the ecotones between each vegetation type. The mean annual temperature (MAT) difference across the gradient is approximately 3 degrees C from bottom to top (MAT 8.5-5.5) and annual precipitation averages from 320 to 530 mm/yr, respectively. The stems of the dominant woody vegetation approach a random spatial pattern across the entire gradient, while the canopy cover shows a clustered pattern. The size of the clusters increases with elevation according to available soil moisture which in turn affects available nutrient resources. The total density of woody species declines with increasing soil moisture along the gl-adient, but total biomass increases. Belowground carbon and nutrient pools change from a heterogenous to a homogenous distribution on either side of the woodlands. Although temperature controls the: seasonal patterns of carbon efflux from the soils, soil moisture appears to be the primary driving variable, but response differs underneath the different dominant species, Similarly, decomposition of dominant litter occurs faster-at the cooler and more moist sites, but differs within sites due to litter quality of the different species. The spatial pattern of these communities provides information on the direction of future changes, The ecological processes that we documented are not statistically different in the ecotones as compared to the: adjoining communities, but are different at sites above the woodland than those below the woodland. We speculate that an increase in MAT will have a major impact on C pools and C sequestering and release processes in these semiarid landscapes. However, the impact will be primarily related to moisture availability rather than direct effects of an increase in temperature. (C) 1998 Elsevier Science B.V.

Indentation size effect and strain rate sensitivity of nanocrystalline Mg-Al alloys

Deformation Behaviour of microcrystalline (mc) and nanocrystalline (nc) Mg-5%Al alloys produced by hot extrusion of ball-milled powders were investigated using instrumented indentation tests. The hardness values of the mc and nc metals exhibited indentation size effect (ISE), with nc alloys showing weaker ISE. The highly localized dislocation activities resulted in a small activation volume, hence enhanced strain rate sensitivity. Relative higher strain rate sensitivity and the negative Hall-Petch Relationship suggested the increasingly important role of grain boundary mediated mechanisms when the grain size decreased to nanometer region.

The role of emotional labour and role stress on burnout and psychological strain in high contact service employees

This study examines the relationships between job demands (in the form of role stressors and emotional management) and employee burnout amongst high contact service employees. Employees in customer facing roles are frequently required to manage overwhelming, conflicting or ambiguous demands, which they may feel ill-equipped to handle. Simultaneously, they must manage the emotions they display towards customers, suppressing some, and expressing others, be they genuine or contrived. If the in-role effort required of employees exceeds their inherent capacity to cope, burnout may result. Burnout, in turn, can have serious detrimental consequences for the psychological well being of employees. We find that both emotional management and role stressors impact burnout. We also confirm that burnout predicts psychological strain. In line with the Job Demands and Resources Model, we examine the mitigating impact of perceived support on these relationships but do not find a significant mitigating impact.

Complete Nucleotide Sequence of Rice Tungro Spherical Virus Genome of a Highly Virulent Strain Vt6

The complete nucleotide sequence of rice tungro spherical virus (RTSV) strain Vt6, originally from Mindanao, the Philippines, with higher virulence to resistant rice cultivars, was determined and compared with the published sequence for the Philippine-type strain A (RTSV-A-Shen). It was reported that RTSV-A was not able to infect a rice resistant cultivar TKM 6 (10). RTSV-Vt6 and RTSV-A-Shen share 90% and 95% homology at nucleotide and amino-acid levels, respectively. The N-terminal leader sequence of RTSV-Vt6 contained a 39-amino acids-region (positions 65 to 103) which was totally different from that of RTSV-A-Shen; the difference resulted from frame shifting by nucleotide insertions and deletions. To confirm the amino-acid sequence differences of the leader polypeptide, the same region was cloned and sequenced using a newly obtained variant of RTSV-type 6, which had been collected in the field of IRRI, and seven field isolates from Mindanao, the Philippines. Since all the sequences of the target region are identical to that of the Vt6 leader polypeptide, the sequence difference in the leader region seems not to correlate with the virulence of Vt6.

Testing and simulation of extruded polystyrene foam at low to moderate strain rates

This paper presents a study into the behaviour of extruded polystyrene foam at low strain rates. The foam is being studied in order assess its potential for use as part of a new innovative design of portable road safety barrier the aim to consume less water and reduce rates of serious injury. The foam was tested at a range of low strain rates, with the stress and strain behaviour of the foam specimens being recorded. The energy absorption capabilities of the foam were assessed as well as the response of the foam to multiple loadings. The experimental data was then used to create a material model of the foam for use in the explicit finite element solver LS-DYNA. Simulations were carried out using the material model which showed excellent correlation between the numerical material model and the experimental data.

Hall-petch relationship and strain rate sensitivity of nanocrystalline Mg - 5wt% A1 alloy

This study investigated the grain size dependence of mechanical properties and deformation mechanisms of microcrystalline (mc) and nanocrystalline (nc: grain size below 100 nm) Mg-5wt% Al alloys. The Hall-Petch relationship was investigated by both instrumented indentation tests and compression tests. The test results from the indentation tests and compression tests match well with each other. The breakdown of Hall-Petch relationship and the elevated strain rate sensitivity (SRS) of present Mg-5wt% Al alloys when the grain size was reduced below 58nm indicated the more significant role of GB mediated mechanisms in plastic deformation process. However, the relatively smaller SRS values compared to GB sliding and coble creep process suggested the plastic deformation in the current study is still dislocation mediated mechanism dominant.

Infinite-horizon policy-gradient estimation

Gradient-based approaches to direct policy search in reinforcement learning have received much recent attention as a means to solve problems of partial observability and to avoid some of the problems associated with policy degradation in value-function methods. In this paper we introduce GPOMDP, a simulation-based algorithm for generating a biased estimate of the gradient of the average reward in Partially Observable Markov Decision Processes (POMDPs) controlled by parameterized stochastic policies. A similar algorithm was proposed by Kimura, Yamamura, and Kobayashi (1995). The algorithm's chief advantages are that it requires storage of only twice the number of policy parameters, uses one free parameter β ∈ [0,1) (which has a natural interpretation in terms of bias-variance trade-off), and requires no knowledge of the underlying state. We prove convergence of GPOMDP, and show how the correct choice of the parameter β is related to the mixing time of the controlled POMDP. We briefly describe extensions of GPOMDP to controlled Markov chains, continuous state, observation and control spaces, multiple-agents, higher-order derivatives, and a version for training stochastic policies with internal states. In a companion paper (Baxter, Bartlett, & Weaver, 2001) we show how the gradient estimates generated by GPOMDP can be used in both a traditional stochastic gradient algorithm and a conjugate-gradient procedure to find local optima of the average reward. ©2001 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.

Exponentiated gradient algorithms for conditional random fields and max-margin Markov Networks

Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of parameters in these models is therefore an important problem, and becomes a key factor when learning from very large data sets. This paper describes exponentiated gradient (EG) algorithms for training such models, where EG updates are applied to the convex dual of either the log-linear or max-margin objective function; the dual in both the log-linear and max-margin cases corresponds to minimizing a convex function with simplex constraints. We study both batch and online variants of the algorithm, and provide rates of convergence for both cases. In the max-margin case, O(1/ε) EG updates are required to reach a given accuracy ε in the dual; in contrast, for log-linear models only O(log(1/ε)) updates are required. For both the max-margin and log-linear cases, our bounds suggest that the online EG algorithm requires a factor of n less computation to reach a desired accuracy than the batch EG algorithm, where n is the number of training examples. Our experiments confirm that the online algorithms are much faster than the batch algorithms in practice. We describe how the EG updates factor in a convenient way for structured prediction problems, allowing the algorithms to be efficiently applied to problems such as sequence learning or natural language parsing. We perform extensive evaluation of the algorithms, comparing them to L-BFGS and stochastic gradient descent for log-linear models, and to SVM-Struct for max-margin models. The algorithms are applied to a multi-class problem as well as to a more complex large-scale parsing task. In all these settings, the EG algorithms presented here outperform the other methods.

Exponentiated gradient algorithms for large-margin structured classification

We consider the problem of structured classification, where the task is to predict a label y from an input x, and y has meaningful internal structure. Our framework includes supervised training of Markov random fields and weighted context-free grammars as special cases. We describe an algorithm that solves the large-margin optimization problem defined in [12], using an exponential-family (Gibbs distribution) representation of structured objects. The algorithm is efficient—even in cases where the number of labels y is exponential in size—provided that certain expectations under Gibbs distributions can be calculated efficiently. The method for structured labels relies on a more general result, specifically the application of exponentiated gradient updates [7, 8] to quadratic programs.