285 resultados para yield function


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Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

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The shoot represents the basic body plan in land plants. It consists of a repeated structure composed of stems and leaves. Whereas vascular plants generate a shoot in their diploid phase, non-vascular plants such as mosses form a shoot (called the gametophore) in their haploid generation. The evolution of regulatory mechanisms or genetic networks used in the development of these two kinds of shoots is unclear. TERMINAL EAR1-like genes have been involved in diploid shoot development in vascular plants. Here, we show that disruption of PpTEL1 from the moss Physcomitrella patens, causes reduced protonema growth and gametophore initiation, as well as defects in gametophore development. Leafy shoots formed on ΔTEL1 mutants exhibit shorter stems with more leaves per shoot, suggesting an accelerated leaf initiation (shortened plastochron), a phenotype shared with the Poaceae vascular plants TE1 and PLA2/LHD2 mutants. Moreover, the positive correlation between plastochron length and leaf size observed in ΔTEL1 mutants suggests a conserved compensatory mechanism correlating leaf growth and leaf initiation rate that would minimize overall changes in plant biomass. The RNA-binding protein encoded by PpTEL1 contains two N-terminus RNA-recognition motifs, and a third C-terminus non-canonical RRM, specific to TEL proteins. Removal of the PpTEL1 C-terminus (including this third RRM) or only 16–18 amino acids within it seriously impairs PpTEL1 function, suggesting a critical role for this third RRM. These results show a conserved function of the RNA-binding PpTEL1 protein in the regulation of shoot development, from early ancestors to vascular plants, that depends on the third TEL-specific RRM.

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OBJECTIVES: There is controversy in the literature regarding the effect of inflammatory bowel disease (IBD) on resting energy expenditure (REE). In many cases this may have resulted from inappropriate adjustment of REE measurements to account for differences in body composition. This article considers how to appropriately adjust measurements of REE for differences in body composition between individuals with IBD. PATIENTS AND METHODS: Body composition, assessed via total body potassium to yield a measure of body cell mass (BCM), and REE measurements were performed in 41 children with Crohn disease and ulcerative colitis in the Royal Children's Hospital, Brisbane, Australia. Log-log regression was used to determine the power function to which BCM should be raised to appropriately adjust REE to account for differences in body composition between children. RESULTS: The appropriate value to "adjust" BCM was found to be 0.49, with a standard error of 0.10. CONCLUSIONS: Clearly, there is a need to adjust for differences in body composition, or at the very least body weight, in metabolic studies in children with IBD. We suggest that raising BCM to the power of 0.5 is both a numerically convenient and a statistically valid way of achieving this aim. Under circumstances in which the measurement of BCM is not available, raising body weight to the power of 0.5 remains appropriate. The important issue of whether REE is changed in cases of IBD can then be appropriately addressed. © 2007 Lippincott Williams & Wilkins, Inc.

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The crystallization of amorphous semiconductors is a strongly exothermic process. Once initiated the release of latent heat can be sufficient to drive a self-sustaining crystallization front through the material in a manner that has been described as explosive. Here, we perform a quantitative in situ study of explosive crystallization in amorphous germanium using dynamic transmission electron microscopy. Direct observations of the speed of the explosive crystallization front as it evolves along a laser-imprinted temperature gradient are used to experimentally determine the complete interface response function (i.e., the temperature-dependent front propagation speed) for this process, which reaches a peak of 16 m/s. Fitting to the Frenkel-Wilson kinetic law demonstrates that the diffusivity of the material locally/immediately in advance of the explosive crystallization front is inconsistent with those of a liquid phase. This result suggests a modification to the liquid-mediated mechanism commonly used to describe this process that replaces the phase change at the leading amorphous-liquid interface with a change in bonding character (from covalent to metallic) occurring in the hot amorphous material.

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Purpose Melanopsin-expressing retinal ganglion cells (mRGCs) have non-image forming functions including mediation of the pupil light reflex (PLR). There is limited knowledge about mRGC function in retinal disease. Initial retinal changes in age-related macular degeneration (AMD) occur in the paracentral region where mRGCs have their highest density, making them vulnerable during disease onset. In this cross-sectional clinical study, we measured the PLR to determine if mRGC function is altered in early stages of macular degeneration. Methods Pupil responses were measured in 8 early AMD patients (AREDS 2001 classification; mean age 72.6 ± 7.2 years, 5M, and 3F) and 12 healthy control participants (mean age 66.6 ± 6.1 years, 8M and 4F) using a custom-built Maxwellian-view pupillometer. Stimuli were 0.5 Hz sinewaves (10 s duration, 35.6° diameter) of short wavelength light (464nm, blue; retinal irradiance = 14.5 log quanta.cm-2.s-1) to produce high melanopsin excitation and of long wavelength light (638nm, red; retinal irradiance = 14.9 log quanta.cm-2.s-1), to bias activation to outer retina and provide a control. Baseline pupil diameter was determined during a 10 s pre-stimulus period. The post illumination pupil response (PIPR) was recorded for 40 s. The 6 s PIPR and maximum pupil constriction were expressed as percentage baseline (M ± SD). Results The blue PIPR was significantly less sustained (p<0.01) in the early AMD group (75.49 ± 7.88%) than the control group (58.28 ± 9.05%). The red PIPR was not significantly different (p>0.05) between the early AMD (84.79 ± 4.03%) and control groups (82.01 ± 5.86%). Maximum constriction amplitude in the early AMD group for blue (43.67 ± 6.35%) and red (48.64 ± 6.49%) stimuli were not significantly different to the control group for blue (39.94 ± 3.66%) and red (44.98 ± 3.15%) stimuli (p>0.05). Conclusions These results are suggestive of inner retinal mRGC deficits in early AMD. This non-invasive, objective measure of pupil responses may provide a new method for quantifying mRGC function and monitoring AMD progression.

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Deriving an estimate of optimal fishing effort or even an approximate estimate is very valuable for managing fisheries with multiple target species. The most challenging task associated with this is allocating effort to individual species when only the total effort is recorded. Spatial information on the distribution of each species within a fishery can be used to justify the allocations, but often such information is not available. To determine the long-term overall effort required to achieve maximum sustainable yield (MSY) and maximum economic yield (MEY), we consider three methods for allocating effort: (i) optimal allocation, which optimally allocates effort among target species; (ii) fixed proportions, which chooses proportions based on past catch data; and (iii) economic allocation, which splits effort based on the expected catch value of each species. Determining the overall fishing effort required to achieve these management objectives is a maximizing problem subject to constraints due to economic and social considerations. We illustrated the approaches using a case study of the Moreton Bay Prawn Trawl Fishery in Queensland (Australia). The results were consistent across the three methods. Importantly, our analysis demonstrated the optimal total effort was very sensitive to daily fishing costs-the effort ranged from 9500-11 500 to 6000-7000, 4000 and 2500 boat-days, using daily cost estimates of $0, $500, $750, and $950, respectively. The zero daily cost corresponds to the MSY, while a daily cost of $750 most closely represents the actual present fishing cost. Given the recent debate on which costs should be factored into the analyses for deriving MEY, our findings highlight the importance of including an appropriate cost function for practical management advice. The approaches developed here could be applied to other multispecies fisheries where only aggregated fishing effort data are recorded, as the literature on this type of modelling is sparse.

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The appealing concept of optimal harvesting is often used in fisheries to obtain new management strategies. However, optimality depends on the objective function, which often varies, reflecting the interests of different groups of people. The aim of maximum sustainable yield is to extract the greatest amount of food from replenishable resources in a sustainable way. Maximum sustainable yield may not be desirable from an economic point of view. Maximum economic yield that maximizes the profit of fishing fleets (harvesting sector) but ignores socio-economic benefits such as employment and other positive externalities. It may be more appropriate to use the maximum economic yield that which is based on the value chain of the overall fishing sector, to reflect better society's interests. How to make more efficient use of a fishery for society rather than fishing operators depends critically on the gain function parameters including multiplier effects and inclusion or exclusion of certain costs. In particular, the optimal effort level based on the overall value chain moves closer to the optimal effort for the maximum sustainable yield because of the multiplier effect. These issues are illustrated using the Australian Northern Prawn Fishery.

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A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.

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Robust estimation often relies on a dispersion function that is more slowly varying at large values than the square function. However, the choice of tuning constant in dispersion functions may impact the estimation efficiency to a great extent. For a given family of dispersion functions such as the Huber family, we suggest obtaining the "best" tuning constant from the data so that the asymptotic efficiency is maximized. This data-driven approach can automatically adjust the value of the tuning constant to provide the necessary resistance against outliers. Simulation studies show that substantial efficiency can be gained by this data-dependent approach compared with the traditional approach in which the tuning constant is fixed. We briefly illustrate the proposed method using two datasets.

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The approach of generalized estimating equations (GEE) is based on the framework of generalized linear models but allows for specification of a working matrix for modeling within-subject correlations. The variance is often assumed to be a known function of the mean. This article investigates the impacts of misspecifying the variance function on estimators of the mean parameters for quantitative responses. Our numerical studies indicate that (1) correct specification of the variance function can improve the estimation efficiency even if the correlation structure is misspecified; (2) misspecification of the variance function impacts much more on estimators for within-cluster covariates than for cluster-level covariates; and (3) if the variance function is misspecified, correct choice of the correlation structure may not necessarily improve estimation efficiency. We illustrate impacts of different variance functions using a real data set from cow growth.

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Prostate cancer is a leading contributor to male cancer-related deaths worldwide. Kallikrein-related peptidases (KLKs) are serine proteases that exhibit deregulated expression in prostate cancer, with KLK3, or prostate specific antigen (PSA), being the widely-employed clinical biomarker for prostate cancer. Other KLKs, such as KLK2, show promise as prostate cancer biomarkers and, additionally, their altered expression has been utilised for the design of KLK-targeted therapies. There is also a large body of in vitro and in vivo evidence supporting their role in cancer-related processes. Here, we review the literature on studies to date investigating the potential of other KLKs, in addition to PSA, as biomarkers and in therapeutic options, as well as their current known functional roles in cancer progression. Increased knowledge of these KLK-mediated functions, including degradation of the extracellular matrix, local invasion, cancer cell proliferation, interactions with fibroblasts, angiogenesis, migration, bone metastasis and tumour growth in vivo, may help define new roles as prognostic biomarkers and novel therapeutic targets for this cancer.

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Background Sensorimotor function is degraded in patients after lower limb arthroplasty. Sensorimotor training is thought to improve sensorimotor skills, however, the optimal training stimulus with regard to volume, frequency, duration, and intensity is still unknown. The aim of this study, therefore, was to firstly quantify the progression of sensorimotor function after total hip (THA) or knee (TKA) arthroplasty and, as second step, to evaluate effects of different sensorimotor training volumes. Methods 58 in-patients during their rehabilitation after THA or TKA participated in this prospective cohort study. Sensorimotor function was assessed using a test battery including measures of stabilization capacity, static balance, proprioception, and gait, along with a self-reported pain and function. All participants were randomly assigned to one of three intervention groups performing sensorimotor training two, four, or six times per week. Outcome measures were taken at three instances, at baseline (pre), after 1.5 weeks (mid) and at the conclusion of the 3 week program (post). Results All measurements showed significant improvements over time, with the exception of proprioception and static balance during quiet bipedal stance which showed no significant main effects for time or intervention. There was no significant effect of sensorimotor training volume on any of the outcome measures. Conclusion We were able to quantify improvements in measures of dynamic, but not static, sensorimotor function during the initial three weeks of rehabilitation following TKA/THA. Although sensorimotor improvements were independent of the training volume applied in the current study, long-term effects of sensorimotor training volume need to be investigated to optimize training stimulus recommendations.

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This paper investigates the stock-recruitment and equilibrium yield dynamics for the two species of tiger prawns (Penaeus esculentus and Penaeus semisulcatus) in Australia's most productive prawn fishery: the Northern Prawn Fishery. Commercial trawl logbooks for 1970-93 and research surveys are used to develop population models for these prawns. A population model that incorporates continuous recruitment is developed. Annual spawning stock and recruitment indices are then estimated from the population model. Spawning stock indices represent the abundance of female prawns that are likely to spawn; recruitment indices represent the abundance of all prawns less than a certain size. The relationships between spawning stock and subsequent recruitment (SRR), between recruitment and subsequent spawning stock (RSR), and between recruitment and commercial catch were estimated through maximum-likelihood models that incorporated autoregressive terms. Yield as a function of fishing effort was estimated by constraining to equilibrium the SRR and RSR. The resulting production model was then used to determine maximum sustainable yield (MSY) and its corresponding fishing effort (f(MSY)). Long-term yield estimates for the two tiger prawn species range between 3700 and 5300 t. The fishing effort at present is close to the level that should produce MSY for both species of tiger prawns. However, current landings, recruitment and spawning stock are below the equilibrium values predicted by the models. This may be because of uncertainty in the spawning stock-recruitment relationships, a change in carrying capacity, biased estimates of fishing effort, unreliable catch statistics, or simplistic assumptions about stock structure. Although our predictions of tiger prawn yields are uncertain, management will soon have to consider new measures to counteract the effects of future increases in fishing effort.

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Indirect and qualitative tests of pancreatic function are commonly used to screen patients with cystic fibrosis for pancreatic insufficiency. In an attempt to develop a more quantitative assessment, we compared the usefulness of measuring serum pancreatic lipase using a newly developed enzyme-linked immunosorbent immunoassay with that of cationic trypsinogen using a radioimmunoassay in the assessment of exocrine pancreatic function in patients with cystic fibrosis. Previously, we have shown neither lipase nor trypsinogen to be of use in assessing pancreatic function prior to 5 years of age because the majority of patients with cystic fibrosis in early infancy have elevated serum levels regardless of pancreatic function. Therefore, we studied 77 patients with cystic fibrosis older than 5 years of age, 41 with steatorrhea and 36 without steatorrhea. In addition, 28 of 77 patients consented to undergo a quantitative pancreatic stimulation test. There was a significant difference between the steatorrheic and nonsteatorrheic patients with the steatorrheic group having lower lipase and trypsinogen values than the nonsteatorrheic group (P < .001). Sensitivities and specificities in detecting steatorrhea were 95% and 86%, respectively, for lipase and 93% and 92%, respectively, for trypsinogen. No correlations were found between the serum levels of lipase and trypsinogen and their respective duodenal concentrations because of abnormally high serum levels of both enzymes found in some nonsteatorrheic patients. We conclude from this study that both serum lipase and trypsinogen levels accurately detect steatorrhea in patients with cystic fibrosis who are older than 5 years but are imprecise indicators of specific pancreatic exocrine function above the level needed for normal fat absorption.