891 resultados para Difference Equations with Maxima


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First-year undergraduate engineering students' understanding of the units of factors and terms in first-order ordinary differential equations used in modelling contexts was investigated using diagnostic quiz questions. Few students appeared to realize that the units of each term in such equations must be the same, or if they did, nevertheless failed to apply that knowledge when needed. In addition, few students were able to determine the units of a proportionality factor in a simple equation. These results indicate that lecturers of modelling courses cannot take this foundational knowledge for granted and should explicitly include it in instruction.

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Purpose: Optometrists are becoming more integrally involved in the diagnosis of and care for glaucoma patients in the UK. The correlation of apparent change in non contact tonometry (NCT) IOP measurement and change in other ocular parameters such as refractive error, corneal curvature, corneal thickness and treatment zone size (data available to optometrists after LASIK) would facilitate care of these patients. Setting: A UK Laser Eye Clinic. Methods: This is a retrospective study study of 200 sequential eyes with myopia with or without astigmatism which underwent LASIK using a Hansatome and an Alcon LADARvision 4000 excimer laser. Refraction keratometry, pachymetry and NCT IOP mesurements were taken before treatmebnt and agian 3 months after treatment. The relationship between these variables anfd teh treatment zones were studied using stepwise multiple regression analysis. Results: There was a mean difference of 5.54mmHg comnparing pre and postoperative NCT IOP. IOP change correlates with refractive error change (P < 0.001), preoperative corneal thickness (P < 0.001) and treatment zone size (P = 0.047). Preoperative corneal thickness correlates with preoperative IOP (P < 0.001) and postoperative IOP (P < 0.001). Using these correlations, the measured difference in NCT IIOP can be predicted preoperatively or postoperatively using derived equations.Conclusion: There is a significant reduction in measured NCT IOP after LASIK. The amount of reduction can be calculated using data acquired by optometrists. This is helpful for opthalmologists and optometrists who co-manage glaucoma patients who have had LASIK or with glaucoma pateints who are consideraing having LASIK.

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Background/Aim - People of south Asian origin have an excessive risk of morbidity and mortality from cardiovascular disease. We examined the effect of ethnicity on known risk factors and analysed the risk of cardiovascular events and mortality in UK south Asian and white Europeans patients with type 2 diabetes over a 2 year period. Methods - A total of 1486 south Asian (SA) and 492 white European (WE) subjects with type 2 diabetes were recruited from 25 general practices in Coventry and Birmingham, UK. Baseline data included clinical history, anthropometry and measurements of traditional risk factors – blood pressure, total cholesterol, HbA1c. Multiple linear regression models were used to examine ethnicity differences in individual risk factors. Ten-year cardiovascular risk was estimated using the Framingham and UKPDS equations. All subjects were followed up for 2 years. Cardiovascular events (CVD) and mortality between the two groups were compared. Findings - Significant differences were noted in risk profiles between both groups. After adjustment for clustering and confounding a significant ethnicity effect remained only for higher HbA1c (0.50 [0.22 to 0.77]; P?=?0.0004) and lower HDL (-0.09 [-0.17 to -0.01]; P?=?0.0266). Baseline CVD history was predictive of CVD events during follow-up for SA (P?difference of 7.4 years (95% CI 1.0 to 13.7 years), P?=?0.023. The adjusted odds ratio of CVD event or death from CVD was greater but not significantly so in SA than in WE (OR 1.4 [0.9 to 2.2]). Limitations - Fewer events in both groups and short period of follow-up are key limitations. Longer follow-up is required to see if the observed differences between the ethnic groups persist. Conclusion - South Asian patients with type 2 diabetes in the UK have a higher cardiovascular risk and present with cardiovascular events at a significantly younger age than white Europeans. Enhanced and ethnicity specific targets and effective treatments are needed if these inequalities are to be reduced.

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Orthonormal polynomials on the real line {pn (λ)} n=0 ... ∞ satisfy the recurrent relation of the form: λn−1 pn−1 (λ) + αn pn (λ) + λn pn+1 (λ) = λpn (λ), n = 0, 1, 2, . . . , where λn > 0, αn ∈ R, n = 0, 1, . . . ; λ−1 = p−1 = 0, λ ∈ C. In this paper we study systems of polynomials {pn (λ)} n=0 ... ∞ which satisfy the equation: αn−2 pn−2 (λ) + βn−1 pn−1 (λ) + γn pn (λ) + βn pn+1 (λ) + αn pn+2 (λ) = λ2 pn (λ), n = 0, 1, 2, . . . , where αn > 0, βn ∈ C, γn ∈ R, n = 0, 1, 2, . . ., α−1 = α−2 = β−1 = 0, p−1 = p−2 = 0, p0 (λ) = 1, p1 (λ) = cλ + b, c > 0, b ∈ C, λ ∈ C. It is shown that they are orthonormal on the real and the imaginary axes in the complex plane ...

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Dubrovin type equations for the N -gap solution of a completely integrable system associated with a polynomial pencil is constructed and then integrated to a system of functional equations. The approach used to derive those results is a generalization of the familiar process of finding the 1-soliton (1-gap) solution by integrating the ODE obtained from the soliton equation via the substitution u = u(x + λt).

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We consider the existence and uniqueness problem for partial differential-functional equations of the first order with the initial condition for which the right-hand side depends on the derivative of unknown function with deviating argument.

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In this paper, we are considered with the optimal control of a schrodinger equation. Based on the formulation for the variation of the cost functional, a gradient-type optimization technique utilizing the finite difference method is then developed to solve the constrained optimization problem. Finally, a numerical example is given and the results show that the method of solution is robust.

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2000 Mathematics Subject Classification: 34K99, 44A15, 44A35, 42A75, 42A63

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2000 Mathematics Subject Classification: 35J40, 49J52, 49J40, 46E30

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2000 Mathematics Subject Classification: Primary 60F17, 60G52, 60G70 secondary 60E07, 62E20.

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2000 Mathematics Subject Classification: 65H10.

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2000 Mathematics Subject Classification: 34C10, 34C15.