864 resultados para Time-varying Constraints


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This paper studies the effect of credit constraints and constraints on transfers between parents and children, on differences in labor and schooling across children within the same household, with an application to gender. When families are unconstrained in these respects, differences in labor supply or education are driven by differences in wages or returns to education. If the family faces an imperfect capital market, the labor supply of each child is inefficient, but differences across children are still driven by comparative advantage. However, if interfamily transfers are constrained so that parents cannot offset inequality between their children, they will favor the human capital accumulation of the more disadvantaged child -generally the one who works more as a child. We use our theory to examine the gender gap in child labor. Using a sample of poor families in Colombia, we conform our predictions among rural households, although this is less clear for urban households. The gender gap is largely explained by the wage gap between girls and boys. Moreover, families with the potential to make capital transfers to adult children (e.g. those with large animals), can compensate adult sons for their greater child labor and reduced educational attainment. In such families, as predicted, the male/female labor gap is greater.

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Simmental × Holstein-Friesian steers were offered four forage diets. These comprised grass silage (G); proportionately 0·67 grass silage, proportionately 0·33 maize silage (GGM); 0·33 grass silage, 0·67 maize silage ( MMG); maize silage ( M) from 424 (s.d. = 11·5) kg to slaughter at a minimum weight of 560 kg. Forages were mixed and offered ad libitum. Steers were offered 2 kg of a concentrate daily, the concentrate being formulated such that all steers had similar crude protein intakes across dietary treatments. A sample of steers was slaughtered at the beginning of the experimental period to allow the calculation of the rate of gain of the carcass and its components. Carcass dissection of a sample of steers allowed the development of a prediction equation of carcass composition based on thoracic limb dissection of all carcasses. Forage dry matter intake and live-weight gain increased linearly as maize silage replaced grass silage in the forage mixture, resulting in improvements in food conversion ratio (all P = 0·001). Killing-out proportion increased with maize silage inclusion ( P < 0·001) but fat and conformation scores did not differ significantly between diets. However, increasing maize inclusion in the diet resulted in a greater weight ( P = 0·05) and proportion ( P = 0·008) of fat in the carcass, and significant increases in internal fat deposition. The inclusion of maize led to a progressive increase in the daily gains of carcass ( P < 0·001), and significant increases in the daily gains of both fat ( P < 0·001) and lean tissue ( P < 0·001). Fat colour was more yellow in cattle given diets G and GGM than diets MMG and M ( P < 0·001) and colour intensity was lower on diet M than the other three diets ( P < 0·001). There were no significant differences in any aspects of eating quality between diets. Therefore, maize silage has the potential to reduce the time taken for finishing beef animals to achieve slaughter weight with no apparent detrimental effects on subsequent meat quality.

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Many time series are measured monthly, either as averages or totals, and such data often exhibit seasonal variability-the values of the series are consistently larger for some months of the year than for others. A typical series of this type is the number of deaths each month attributed to SIDS (Sudden Infant Death Syndrome). Seasonality can be modelled in a number of ways. This paper describes and discusses various methods for modelling seasonality in SIDS data, though much of the discussion is relevant to other seasonally varying data. There are two main approaches, either fitting a circular probability distribution to the data, or using regression-based techniques to model the mean seasonal behaviour. Both are discussed in this paper.

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Aim The Mediterranean region is a species-rich area with a complex geographical history. Geographical barriers have been removed and restored due to sea level changes and local climatic change. Such barriers have been proposed as a plausible mechanism driving the high levels of speciation and endemism in the Mediterranean basin. This raises the fundamental question: is allopatric isolation the mechanism by which speciation occurs? This study explores the potential driving influence of palaeo-geographical events on the speciation of Cyclamen (Myrsinaceae), a group with most species endemic to the Mediterranean region. Cyclamen species have been shown experimentally to have few genetic barriers to hybridization. Location The Mediterranean region, including northern Africa, extending eastwards to the Black Sea coast. Methods A generic level molecular phylogeny of Myrsinaceae and Primulaceae is constructed, using Bayesian approximation, to produce a secondary age estimate for the stem lineage of Cyclamen. This estimate is used to calibrate temporally an infrageneric phylogeny of Cyclamen, built with nrDNA ITS, cpDNA trnL-F and cpDNA rps16 sequences. A biogeographical analysis of Cyclamen is performed using dispersal-vicariance analysis. Results The emergence of the Cyclamen stem lineage is estimated at 30.1-29.2 Ma, and the crown divergence at 12.9-12.2 Ma. The average age of Cyclamen species is 3.7 Myr. Every pair of sister species have mutually exclusive, allopatric distributions relative to each other. This pattern appears typical of divergence events throughout the evolutionary history of the genus. Main conclusions Geographical barriers, such as the varying levels of the Mediterranean Sea, are the most plausible explanation for speciation events throughout the phylogenetic history of Cyclamen. The genus demonstrates distributional patterns congruent with the temporally reticulate palaeogeography of the Mediterranean region.

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The combination of model predictive control based on linear models (MPC) with feedback linearization (FL) has attracted interest for a number of years, giving rise to MPC+FL control schemes. An important advantage of such schemes is that feedback linearizable plants can be controlled with a linear predictive controller with a fixed model. Handling input constraints within such schemes is difficult since simple bound contraints on the input become state dependent because of the nonlinear transformation introduced by feedback linearization. This paper introduces a technique for handling input constraints within a real time MPC/FL scheme, where the plant model employed is a class of dynamic neural networks. The technique is based on a simple affine transformation of the feasible area. A simulated case study is presented to illustrate the use and benefits of the technique.

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This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii) object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed. Copyright (C) 2007 Hindawi Publishing Corporation. All rights reserved.

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In this paper we develop an asymptotic scheme to approximate the trapped mode solutions to the time harmonic wave equation in a three-dimensional waveguide with a smooth but otherwise arbitrarily shaped cross section and a single, slowly varying `bulge', symmetric in the longitudinal direction. Extending the work in Biggs (2012), we first employ a WKBJ-type ansatz to identify the possible quasi-mode solutions which propagate only in the thicker region, and hence find a finite cut-on region of oscillatory behaviour and asymptotic decay elsewhere. The WKBJ expansions are used to identify a turning point between the cut-on and cut-on regions. We note that the expansions are nonuniform in an interior layer centred on this point, and we use the method of matched asymptotic expansions to connect the cut-on and cut-on regions within this layer. The behaviour of the expansions within the interior layer then motivates the construction of a uniformly valid asymptotic expansion. Finally, we use this expansion and the symmetry of the waveguide around the longitudinal centre, x = 0, to extract trapped mode wavenumbers, which are compared with those found using a numerical scheme and seen to be extremely accurate, even to relatively large values of the small parameter.

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This paper investigates the effect of time offset errors on the partial parallel interference canceller (PIC) and compares the performance of it against that of the standard PIC. The BER performances of the standard and partial interference cancellers are simulated in a near far environment with varying time offset errors. These simulations indicate that whilst timing errors significantly affect the performance of both these schemes, they do not diminish the gains that are realised by the partial PIC over that of the standard PIC.

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OBJECTIVE: Substrate and hormone responses to meals of differing fat content were evaluated in normal subjects in order to investigate mechanisms underlying the regulation of postprandial lipoprotein concentration. DESIGN: A randomised cross-over study with three different meals on three occasions. SETTING: Free-living subjects associated with Surrey University. SUBJECTS: Ten male volunteers (aged 18-23 years) were recruited. INTERVENTIONS: Three test meals containing 20, 40 or 80 g fat but identical carbohydrate and protein content were randomly allocated to volunteers. MAJOR OUTCOME MEASURES: Pre- and postprandial blood samples were taken for the analysis of plasma triacylglycerol, non-esterified fatty acids, glucose, immunoreactive insulin and glucose-dependent insulinotrophic polypeptide levels and postheparin lipoprotein lipase activity measurements. RESULTS: Peak triacylglycerol concentrations and lipoprotein lipase activity measurements were significantly higher following the 80 g than the 20 g fat meal (P = 0.009 and P = 0.049 respectively). Areas under the glucose-dependent insulinotrophic polypeptide time-response concentration curves were significantly higher following the 80 g compared with the 20 g fat meal (P = 0.04), but no differences in insulin response to the meals were seen. The 30-360 min decrease in the non-esterified fatty acid concentration was less following the 80 g than the 20 g meal (P = 0.001). CONCLUSIONS: The results suggest that glucose-dependent insulinotrophic polypeptide may mediate increased lipoprotein lipase activity in response to fat-containing meals and may play a role in circulating lipoprotein homeostasis. This mechanism may be overloaded with high fat meals with adverse consequences on circulating triacylglycerol and NEFA concentrations.

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Pregnant rats were given control (46 mg iron/kg, 61 mg zinc/kg), low-Zn (6.9 mg Zn/kg) or low-Zn plus Fe (168 mg Fe/kg) diets from day 1 of pregnancy. The animals were allowed to give birth and parturition times recorded. Exactly 24 h after the end of parturition the pups were killed and analysed for water, fat, protein, Fe and Zn contents and the mothers' haemoglobin (Hb) and packed cell volume (PCV) were measured. There were no differences in weight gain or food intakes throughout pregnancy. Parturition times were similar (mean time 123 (SE 15) min) and there were no differences in the number of pups born. Protein, water and fat contents of the pups were similar but the low-Zn Fe-supplemented group had higher pup Fe than the low-Zn unsupplemented group, and the control group had higher pup Zn than both the low-Zn groups. The low-Zn groups had a greater incidence of haemorrhaged or deformed pups, or both, than the controls. Pregnant rats were given diets of adequate Zn level (40 mg/kg) but with varying Fe:Zn (0.8, 1.7, 2.9, 3.7). Zn retention from the diet was measured using 65Zn as an extrinsic label on days 3, 10 and 17 of pregnancy with a whole-body gamma-counter. A group of non-pregnant rats was also included as controls. The 65Zn content of mothers and pups was measured 24-48 h after birth and at 14, 21 and 24 d of age. In all groups Zn retention was highest from the first meal, fell in the second meal and then rose in the third meal of the pregnant but not the non-pregnant rats. There were no differences between the groups given diets of varying Fe:Zn level. Approximately 25% of the 65Zn was transferred from the mothers to the pups by the time they were 48 h old, and a further 17% during the first 14 d of lactation. The pup 65Zn content did not significantly increase after the first 20 d of lactation but the maternal 65Zn level continued to fall gradually.

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Decision theory is the study of models of judgement involved in, and leading to, deliberate and (usually) rational choice. In real estate investment there are normative models for the allocation of assets. These asset allocation models suggest an optimum allocation between the respective asset classes based on the investors’ judgements of performance and risk. Real estate is selected, as other assets, on the basis of some criteria, e.g. commonly its marginal contribution to the production of a mean variance efficient multi asset portfolio, subject to the investor’s objectives and capital rationing constraints. However, decisions are made relative to current expectations and current business constraints. Whilst a decision maker may believe in the required optimum exposure levels as dictated by an asset allocation model, the final decision may/will be influenced by factors outside the parameters of the mathematical model. This paper discusses investors' perceptions and attitudes toward real estate and highlights the important difference between theoretical exposure levels and pragmatic business considerations. It develops a model to identify “soft” parameters in decision making which will influence the optimal allocation for that asset class. This “soft” information may relate to behavioural issues such as the tendency to mirror competitors; a desire to meet weight of money objectives; a desire to retain the status quo and many other non-financial considerations. The paper aims to establish the place of property in multi asset portfolios in the UK and examine the asset allocation process in practice, with a view to understanding the decision making process and to look at investors’ perceptions based on an historic analysis of market expectation; a comparison with historic data and an analysis of actual performance.

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Identifying a periodic time-series model from environmental records, without imposing the positivity of the growth rate, does not necessarily respect the time order of the data observations. Consequently, subsequent observations, sampled in the environmental archive, can be inversed on the time axis, resulting in a non-physical signal model. In this paper an optimization technique with linear constraints on the signal model parameters is proposed that prevents time inversions. The activation conditions for this constrained optimization are based upon the physical constraint of the growth rate, namely, that it cannot take values smaller than zero. The actual constraints are defined for polynomials and first-order splines as basis functions for the nonlinear contribution in the distance-time relationship. The method is compared with an existing method that eliminates the time inversions, and its noise sensitivity is tested by means of Monte Carlo simulations. Finally, the usefulness of the method is demonstrated on the measurements of the vessel density, in a mangrove tree, Rhizophora mucronata, and the measurement of Mg/Ca ratios, in a bivalve, Mytilus trossulus.

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Previous studies have reported that cheese curd syneresis kinetics can be monitored by dilution of chemical tracers, such as Blue Dextran, in whey. The objective of this study was to evaluate an improved tracer method to monitor whey volumes expelled over time during syneresis. Two experiments with different ranges of milk fat (0-5% and 2.3-3.5%) were carried out in an 11 L double-O laboratory scale cheese vat. Tracer was added to the curd-whey mixture during the cutting phase of cheese making and samples were taken at 10 min intervals up to 75 min after cutting. The volume of whey expelled was measured gravimetrically and the dilution of tracer in the whey was measured by absorbance at 620 nm. The volumes of whey expelled were significantly reduced at higher milk fat levels. Whey yield was predicted with a SEP ranging from 3.2 to 6.3 g whey/100 mL of milk and a CV ranging from 2.03 to 2.7% at different milk fat levels.

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This paper describes an experimental application of constrained predictive control and feedback linearisation based on dynamic neural networks. It also verifies experimentally a method for handling input constraints, which are transformed by the feedback linearisation mappings. A performance comparison with a PID controller is also provided. The experimental system consists of a laboratory based single link manipulator arm, which is controlled in real time using MATLAB/SIMULINK together with data acquisition equipment.

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Adaptive methods which “equidistribute” a given positive weight function are now used fairly widely for selecting discrete meshes. The disadvantage of such schemes is that the resulting mesh may not be smoothly varying. In this paper a technique is developed for equidistributing a function subject to constraints on the ratios of adjacent steps in the mesh. Given a weight function $f \geqq 0$ on an interval $[a,b]$ and constants $c$ and $K$, the method produces a mesh with points $x_0 = a,x_{j + 1} = x_j + h_j ,j = 0,1, \cdots ,n - 1$ and $x_n = b$ such that\[ \int_{xj}^{x_{j + 1} } {f \leqq c\quad {\text{and}}\quad \frac{1} {K}} \leqq \frac{{h_{j + 1} }} {{h_j }} \leqq K\quad {\text{for}}\, j = 0,1, \cdots ,n - 1 . \] A theoretical analysis of the procedure is presented, and numerical algorithms for implementing the method are given. Examples show that the procedure is effective in practice. Other types of constraints on equidistributing meshes are also discussed. The principal application of the procedure is to the solution of boundary value problems, where the weight function is generally some error indicator, and accuracy and convergence properties may depend on the smoothness of the mesh. Other practical applications include the regrading of statistical data.