7 resultados para errors-in-variables model

em Universidad de Alicante


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Background: Refractive error is defined as the inability of the eye to bring parallel rays of light into focus on the retina, resulting in nearsightedness (myopia), farsightedness (Hyperopia) or astigmatism. Uncorrected refractive error in children is associated with increased morbidity and reduced educational opportunities. Vision screening (VS) is a method for identifying children with visual impairment or eye conditions likely to lead to visual impairment. Objective: To analyze the utility of vision screening conducted by teachers and to contribute to a better estimation of the prevalence of childhood refractive errors in Apurimac, Peru. Design: A pilot vision screening program in preschool (Group I) and elementary school children (Group II) was conducted with the participation of 26 trained teachers. Children whose visual acuity was<6/9 [20/30] (Group I) and≤6/9 (Group II) in one or both eyes, measured with the Snellen Tumbling E chart at 6 m, were referred for a comprehensive eye exam. Specificity and positive predictive value to detect refractive error were calculated against clinical examination. Program assessment with participants was conducted to evaluate outcomes and procedures. Results: A total sample of 364 children aged 3–11 were screened; 45 children were examined at Centro Oftalmológico Monseñor Enrique Pelach (COMEP) Eye Hospital. Prevalence of refractive error was 6.2% (Group I) and 6.9% (Group II); specificity of teacher vision screening was 95.8% and 93.0%, while positive predictive value was 59.1% and 47.8% for each group, respectively. Aspects highlighted to improve the program included extending training, increasing parental involvement, and helping referred children to attend the hospital. Conclusion: Prevalence of refractive error in children is significant in the region. Vision screening performed by trained teachers is a valid intervention for early detection of refractive error, including screening of preschool children. Program sustainability and improvements in education and quality of life resulting from childhood vision screening require further research.

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Background: Retinitis pigmentosa is a heterogeneous group of inherited neurodegenerative retinal disorders characterized by a progressive peripheral vision loss and night vision difficulties, subsequently leading to central vision impairment. Chronic microglia activation is associated with various neurodegenerative diseases including retinitis pigmentosa. The objective of this study was to quantify microglia activation in the retina of P23H rats, an animal model of retinitis pigmentosa, and to evaluate the therapeutic effects of TUDCA (tauroursodeoxycholic acid), which has been described as a neuroprotective compound. Methods: For this study, homozygous P23H line 3 and Sprague-Dawley (SD) rats were injected weekly with TUDCA (500 mg/kg, ip) or vehicle (saline) from 20 days to 4 months old. Vertical retinal sections and whole-mount retinas were immunostained for specific markers of microglial cells (anti-CD11b, anti-Iba1 and anti-MHC-II). Microglial cell morphology was analyzed and the number of retinal microglial was quantified. Results: Microglial cells in the SD rat retinas were arranged in regular mosaics homogenously distributed within the plexiform and ganglion cell layers. In the P23H rat retina, microglial cells increased in number in all layers compared with control SD rat retinas, preserving the regular mosaic distribution. In addition, a large number of amoeboid CD11b-positive cells were observed in the P23H rat retina, even in the subretinal space. Retinas of TUDCA-treated P23H animals exhibited lower microglial cell number in all layers and absence of microglial cells in the subretinal space. Conclusions: These results report novel TUDCA anti-inflammatory actions, with potential therapeutic implications for neurodegenerative diseases, including retinitis pigmentosa.

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The use of microprocessor-based systems is gaining importance in application domains where safety is a must. For this reason, there is a growing concern about the mitigation of SEU and SET effects. This paper presents a new hybrid technique aimed to protect both the data and the control-flow of embedded applications running on microprocessors. On one hand, the approach is based on software redundancy techniques for correcting errors produced in the data. On the other hand, control-flow errors can be detected by reusing the on-chip debug interface, existing in most modern microprocessors. Experimental results show an important increase in the system reliability even superior to two orders of magnitude, in terms of mitigation of both SEUs and SETs. Furthermore, the overheads incurred by our technique can be perfectly assumable in low-cost systems.

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Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

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Purpose: To calculate theoretically the errors in the estimation of corneal power when using the keratometric index (nk) in eyes that underwent laser refractive surgery for the correction of myopia and to define and validate clinically an algorithm for minimizing such errors. Methods: Differences between corneal power estimation by using the classical nk and by using the Gaussian equation in eyes that underwent laser myopic refractive surgery were simulated and evaluated theoretically. Additionally, an adjusted keratometric index (nkadj) model dependent on r1c was developed for minimizing these differences. The model was validated clinically by retrospectively using the data from 32 myopic eyes [range, −1.00 to −6.00 diopters (D)] that had undergone laser in situ keratomileusis using a solid-state laser platform. The agreement between Gaussian (PGaussc) and adjusted keratometric (Pkadj) corneal powers in such eyes was evaluated. Results: It was found that overestimations of corneal power up to 3.5 D were possible for nk = 1.3375 according to our simulations. The nk value to avoid the keratometric error ranged between 1.2984 and 1.3297. The following nkadj models were obtained: nkadj= −0.0064286r1c + 1.37688 (Gullstrand eye model) and nkadj = −0.0063804r1c + 1.37806 (Le Grand). The mean difference between Pkadj and PGaussc was 0.00 D, with limits of agreement of −0.45 and +0.46 D. This difference correlated significantly with the posterior corneal radius (r = −0.94, P < 0.01). Conclusions: The use of a single nk for estimating the corneal power in eyes that underwent a laser myopic refractive surgery can lead to significant errors. These errors can be minimized by using a variable nk dependent on r1c.

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This paper introduces a new mathematical model for the simultaneous synthesis of heat exchanger networks (HENs), wherein the handling pressure of process streams is used to enhance the heat integration. The proposed approach combines generalized disjunctive programming (GDP) and mixed-integer nonlinear programming (MINLP) formulation, in order to minimize the total annualized cost composed by operational and capital expenses. A multi-stage superstructure is developed for the HEN synthesis, assuming constant heat capacity flow rates and isothermal mixing, and allowing for streams splits. In this model, the pressure and temperature of streams must be treated as optimization variables, increasing further the complexity and difficulty to solve the problem. In addition, the model allows for coupling of compressors and turbines to save energy. A case study is performed to verify the accuracy of the proposed model. In this example, the optimal integration between the heat and work decreases the need for thermal utilities in the HEN design. As a result, the total annualized cost is also reduced due to the decrease in the operational expenses related to the heating and cooling of the streams.

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In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process.