74 resultados para fast axis
Resumo:
Asynchronous Optical Sampling (ASOPS) [1,2] and frequency comb spectrometry [3] based on dual Ti:saphire resonators operated in a master/slave mode have the potential to improve signal to noise ratio in THz transient and IR sperctrometry. The multimode Brownian oscillator time-domain response function described by state-space models is a mathematically robust framework that can be used to describe the dispersive phenomena governed by Lorentzian, Debye and Drude responses. In addition, the optical properties of an arbitrary medium can be expressed as a linear combination of simple multimode Brownian oscillator functions. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing the recorded THz transients in the time or frequency domain will be outlined [4,5]. Since a femtosecond duration pulse is capable of persistent excitation of the medium within which it propagates, such approach is perfectly justifiable. Several de-noising routines based on system identification will be shown. Furthermore, specifically developed apodization structures will be discussed. These are necessary because due to dispersion issues, the time-domain background and sample interferograms are non-symmetrical [6-8]. These procedures can lead to a more precise estimation of the complex insertion loss function. The algorithms are applicable to femtosecond spectroscopies across the EM spectrum. Finally, a methodology for femtosecond pulse shaping using genetic algorithms aiming to map and control molecular relaxation processes will be mentioned.
Resumo:
Comparative analyses of survival senescence by using life tables have identified generalizations including the observation that mammals senesce faster than similar-sized birds. These generalizations have been challenged because of limitations of life-table approaches and the growing appreciation that senescence is more than an increasing probability of death. Without using life tables, we examine senescence rates in annual individual fitness using 20 individual-based data sets of terrestrial vertebrates with contrasting life histories and body size. We find that senescence is widespread in the wild and equally likely to occur in survival and reproduction. Additionally, mammals senesce faster than birds because they have a faster life history for a given body size. By allowing us to disentangle the effects of two major fitness components our methods allow an assessment of the robustness of the prevalent life-table approach. Focusing on one aspect of life history - survival or recruitment - can provide reliable information on overall senescence.
Resumo:
This study investigated possible relationships between measurements of the somatotrophic axis in pre-pubertal dairy calves and subsequent milk yields. Endogenous growth hormone (GH) release was measured through a fed and fasted period in fifty 6-month-old Holstein-Friesian heifers and they were then challenged with growth hormone-releasing factor (GRF) to assess their GH release pattern. Insulin-like growth factor-I (IGF-I), insulin and glucose concentrations were measured in relation to time of feeding. Cows were subsequently monitored through their first three lactations to record peak and 305-day milk yields. In the first lactation, milk energy output for the first 120 days of lactation was also calculated. The mean 305-day milk yield increased from 7417 +/- 191 kg in the first lactation (n = 37) to 8749 +/- 252 kg in the third (n = 25). There were no significant relationships between any measures of GH secretion and peak or 305-day yield in any lactation. A highly significant positive relationship was established between the GH peak measured 10 min post-GRF challenge and 120-day milk energy values in the first lactation. This relationship was, however, only present in the subpopulation of 12 cows culled after one or two lactations and was absent in the 25 animals remaining for the third lactation. There were no significant relationships between pre-pubertal IGF-I and fed or fasted insulin or glucose concentrations and any subsequent measurement of yield. The usefulness of GH secretagogue challenges in calves as a predictive test for future milk production is thus limited but may have some bearing on nutrient partitioning and longevity. (c) 2005 Elsevier Inc. All rights reserved.
Resumo:
The term microfibril angle (MFA) in wood science refers to the angle between the direction of the helical windings of cellulose microfibrils in the secondary cell wall of fibres and tracheids and the long axis of cell. Technologically, it is usually applied to the orientation of cellulose microfibrils in the S2 layer that makes up the greatest proportion of the wall thickness, since it is this which most affects the physical properties of wood. This review describes the organisation of the cellulose component of the secondary wall of fibres and tracheids and the various methods that have been used for the measurement of MFA. It considers the variation of MFA within the tree and the biological reason for the large differences found between juvenile (or core) wood and mature (or outer) wood. The ability of the tree to vary MFA in response to environmental stress, particularly in reaction wood, is also described. Differences in MFA have a profound effect on the properties of wood, in particular its stiffness. The large MFA in juvenile wood confers low stiffness and gives the sapling the flexibility it needs to survive high winds without breaking. It also means, however, that timber containing a high proportion of juvenile wood is unsuitable for use as high-grade structural timber. This fact has taken on increasing importance in view of the trend in forestry towards short rotation cropping of fast grown species. These trees at harvest may contain 50% or more of timber with low stiffness and therefore, low economic value. Although they are presently grown mainly for pulp, pressure for increased timber production means that ways will be sought to improve the quality of their timber by reducing juvenile wood MFA. The mechanism by which the orientation of microfibril deposition is controlled is still a matter of debate. However, the application of molecular techniques is likely to enable modification of this process. The extent to which these techniques should be used to improve timber quality by reducing MFA in juvenile wood is, however, uncertain, since care must be taken to avoid compromising the safety of the tree.
Resumo:
This study used the novel approach of statistical modelling to investigate the control of hypothalamic-pituitary-adrenal (HPA) axis and quantify temporal relationships between hormones. Two experimental paradigms were chosen, insulin-induced hypoglycaemia and 2 h transport, to assess differences in control between noncognitive and cognitive stimuli. Vasopressin and corticotropin-releasing hormone (CRH) were measured in hypophysial portal plasma, and adrenocorticotropin hormone (ACTH) and cortisol in jugular plasma of conscious sheep, and deconvolution analysis was used to calculate secretory rates, before modelling. During hypoglycaemia, the relationship between plasma glucose and vasopressin or CRH was best described by log(10) transforming variables (i.e. a positive power-curve relationship). A negative-feedback relationship with log(10) cortisol concentration 2 h previously was detected. Analysis of the 'transport' stimulus suggested that the strength of the perceived stimulus decreased over time after accounting for cortisol facilitation and negative-feedback. The time course of vasopressin and CRH responses to each stimulus were different However, at the pituitary level, the data suggested that log(10) ACTH secretion rate was related to log(10) vasopressin and CRH concentrations with very similar regression coefficients and an identical ratio of actions (2.3 : 1) for both stimuli. Similar magnitude negative-feedback effects of log(10) cortisol at -110 min (hypoglycaemia) or -40 min (transport) were detected, and both models contained a stimulatory relationship with cortisol at 0 min (facilitation). At adrenal gland level, cortisol secretory rates were related to simultaneously measured untransformed ACTH concentration but the regression coefficient for the hypoglycaemia model was 2.5-fold greater than for transport. No individual sustained maximum cortisol secretion for longer than 20 min during hypoglycaemia and 40 min during transport. These unique models demonstrate that corticosteroid negative-feedback is a significant control mechanism at both the pituitary and hypothalamus. The amplitude of HPA response may be related to stimulus intensity and corticosteroid negative-feedback, while duration depended on feedback alone.
Resumo:
The term microfibril angle (MFA) in wood science refers to the angle between the direction of the helical windings of cellulose microfibrils in the secondary cell wall of fibres and tracheids and the long axis of cell. Technologically, it is usually applied to the orientation of cellulose microfibrils in the S2 layer that makes up the greatest proportion of the wall thickness, since it is this which most affects the physical properties of wood. This review describes the organisation of the cellulose component of the secondary wall of fibres and tracheids and the various methods that have been used for the measurement of MFA. It considers the variation of MFA within the tree and the biological reason for the large differences found between juvenile (or core) wood and mature (or outer) wood. The ability of the tree to vary MFA in response to environmental stress, particularly in reaction wood, is also described. Differences in MFA have a profound effect on the properties of wood, in particular its stiffness. The large MFA in juvenile wood confers low stiffness and gives the sapling the flexibility it needs to survive high winds without breaking. It also means, however, that timber containing a high proportion of juvenile wood is unsuitable for use as high-grade structural timber. This fact has taken on increasing importance in view of the trend in forestry towards short rotation cropping of fast grown species. These trees at harvest may contain 50% or more of timber with low stiffness and therefore, low economic value. Although they are presently grown mainly for pulp, pressure for increased timber production means that ways will be sought to improve the quality of their timber by reducing juvenile wood MFA. The mechanism by which the orientation of microfibril deposition is controlled is still a matter of debate. However, the application of molecular techniques is likely to enable modification of this process. The extent to which these techniques should be used to improve timber quality by reducing MFA in juvenile wood is, however, uncertain, since care must be taken to avoid compromising the safety of the tree.
Resumo:
The relative contributions of slow and fast (online) components in a modified emotional Stroop task were evaluated. The slow component, neglected in previous research, was shown to lead to the prediction of a reversed emotional intrusion effect using pseudorandomly mixed negative and neutral stimuli. This prediction was supported in Experiments 1 and 2. In Experiments 3 and 4, a new paradigm was developed that allowed a more direct observation of the nature of disruptive effects from negative stimuli. The results provided a clear demonstration of the presence of the slow component. The fast component, which has generally been assumed to be the source of the interference, was shown, in fact, to have little or no role in the disruption.
Resumo:
This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of size two for a lower hardware solution while maintaining similar input-output characteristic to the algorithm. The blocked solution, here referred to as B2P algorithm, is obtained using graph theory and retiming methods. Verification approaches were exercised to show that prediction performances obtained from the FPP and B2P algorithms differ within one mis-prediction per thousand instructions using a known framework for branch prediction evaluation. For a chosen FPGA device, circuits generated from the B2P algorithm showed average area savings of over 25% against circuits for the FPP algorithm with similar time performances thus making the proposed blocked predictor superior from a practical viewpoint.
Resumo:
This paper develops cycle-level FPGA circuits of an organization for a fast path-based neural branch predictor Our results suggest that practical sizes of prediction tables are limited to around 32 KB to 64 KB in current FPGA technology due mainly to FPGA area of logic resources to maintain the tables. However the predictor scales well in terms of prediction speed. Table sizes alone should not be used as the only metric for hardware budget when comparing neural-based predictor to predictors of totally different organizations. This paper also gives early evidence to shift the attention on to the recovery from mis-prediction latency rather than on prediction latency as the most critical factor impacting accuracy of predictions for this class of branch predictors.
Resumo:
In order to ease control, the links between actuators and robotic limbs are generally made to be as stiff as possible. This is in contrast to natural limbs, where compliance is present. Springs have been added to the drive train between the actuator and load to imitate this natural compliance. The majority of these springs have been in series between the actuator and load. However, a more biologically inspired approach is taken, here springs have been used in parallel to oppose each other. The paper will describe the application of parallel extension springs in a robot arm in order to give it compliance. Advantages and disadvantages of this application are discussed along with various control strategies.
Resumo:
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for data represented in multidimensional input spaces. In this paper, we describe Fast Learning SOM (FLSOM) which adopts a learning algorithm that improves the performance of the standard SOM with respect to the convergence time in the training phase. We show that FLSOM also improves the quality of the map by providing better clustering quality and topology preservation of multidimensional input data. Several tests have been carried out on different multidimensional datasets, which demonstrate better performances of the algorithm in comparison with the original SOM.
Resumo:
In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.
Resumo:
We propose a simple yet computationally efficient construction algorithm for two-class kernel classifiers. In order to optimise classifier's generalisation capability, an orthogonal forward selection procedure is used to select kernels one by one by minimising the leave-one-out (LOO) misclassification rate directly. It is shown that the computation of the LOO misclassification rate is very efficient owing to orthogonalisation. Examples are used to demonstrate that the proposed algorithm is a viable alternative to construct sparse two-class kernel classifiers in terms of performance and computational efficiency.
Resumo:
We propose a simple and computationally efficient construction algorithm for two class linear-in-the-parameters classifiers. In order to optimize model generalization, a forward orthogonal selection (OFS) procedure is used for minimizing the leave-one-out (LOO) misclassification rate directly. An analytic formula and a set of forward recursive updating formula of the LOO misclassification rate are developed and applied in the proposed algorithm. Numerical examples are used to demonstrate that the proposed algorithm is an excellent alternative approach to construct sparse two class classifiers in terms of performance and computational efficiency.