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Antonio Vela - One of the best experts on this subject based on the ideXlab platform.

  • aortic intima media thickness and aortic diameter in small for gestational age and growth restricted fetuses
    PLOS ONE, 2015
    Co-Authors: Dolores M Gomezroig, Laura Guirado, Mireia Fernandezarias, Edurne Mazarico, Esther Valladares, Antonio Vela
    Abstract:

    Abstract OBJECTIVE: The objective of this study is to measure aortic intima-media thickness (aIMT) and aortic diameter (AD) in appropriate for gestational age (AGA) fetuses, small for gestational age (SGA) fetuses, and intrauterine growth restricted (IUGR) fetuses. METHODS: Case-control study performed between June 2011 and June 2012. Forty-nine AGA fetuses, 40 SGA fetuses, and 35 IUGR fetuses underwent concomitant measurement of aIMT and AD at a mean gestational age of 34.4 weeks. RESULTS: Median aIMT was higher in fetuses with IUGR (0.504 mm [95%CI: 0.477-0.530 mm]), than in SGA fetuses (0.466 mm [95% CI: 0.447-0.485 mm]), and AGA fetuses (0.471 mm [95% CI: 0.454-0.488 mm]) (p = 0.023). Mean AD was significantly lower in fetuses with IUGR (4.451 mm [95% CI: 4.258-4.655 mm]), than in AGA fetuses (4.74 mm [95% CI: 4.63-4.843 mm]) (p = 0.028). CONCLUSIONS: Growth restricted fetuses have a thicker aortic wall than AGA and SGA fetuses, which possibly represents preclinical atherosclerosis and a predisposition to later cardiovascular disease.

  • aortic intima media thickness and aortic diameter in small for gestational age and growth restricted fetuses
    PLOS ONE, 2015
    Co-Authors: Dolores M Gomezroig, Laura Guirado, Mireia Fernandezarias, Edurne Mazarico, Esther Valladares, Antonio Vela
    Abstract:

    Abstract OBJECTIVE: The objective of this study is to measure aortic intima-media thickness (aIMT) and aortic diameter (AD) in appropriate for gestational age (AGA) fetuses, small for gestational age (SGA) fetuses, and intrauterine growth restricted (IUGR) fetuses. METHODS: Case-control study performed between June 2011 and June 2012. Forty-nine AGA fetuses, 40 SGA fetuses, and 35 IUGR fetuses underwent concomitant measurement of aIMT and AD at a mean gestational age of 34.4 weeks. RESULTS: Median aIMT was higher in fetuses with IUGR (0.504 mm [95%CI: 0.477-0.530 mm]), than in SGA fetuses (0.466 mm [95% CI: 0.447-0.485 mm]), and AGA fetuses (0.471 mm [95% CI: 0.454-0.488 mm]) (p = 0.023). Mean AD was significantly lower in fetuses with IUGR (4.451 mm [95% CI: 4.258-4.655 mm]), than in AGA fetuses (4.74 mm [95% CI: 4.63-4.843 mm]) (p = 0.028). CONCLUSIONS: Growth restricted fetuses have a thicker aortic wall than AGA and SGA fetuses, which possibly represents preclinical atherosclerosis and a predisposition to later cardiovascular disease.

Jyhhorng Chou - One of the best experts on this subject based on the ideXlab platform.

  • optimal design of digital iir filters by using hybrid taguchi genetic algorithm
    IEEE Transactions on Industrial Electronics, 2006
    Co-Authors: Jinntsong Tsai, Jyhhorng Chou, Tungkuan Liu
    Abstract:

    A hybrid Taguchi genetic algorithm (HTGA) is applied in this paper to solve the problem of designing optimal digital infinite-impulse response (IIR) filters. The HTGA approach is a method of combining the traditional GA (TGA), which has a powerful global exploration capability, with the Taguchi method, which can exploit the optimum offspring. The Taguchi method is inserted between crossover and mutation operations of a TGA. Based on minimizing the L/sub p/-norm approximation error and minimizing the ripple magnitudes of both passband and stopband, a multicriterion combination is employed as the design criterion to obtain the optimal IIR filter that can fit different performance requirements. The proposed HTGA approach is effectively applied to solve the multiparameter and multicriterion optimization problems of designing the digital low-pass (LP), high-pass (HP), bandpass (BP), and bandstop (BS) filters. In these studied problems, there are many parameters and numerous local optima so that these studied problems are challenging enough for evaluating the performances of any proposed GA-based approaches. The computational experiments show that the proposed HTGA approach can obtain better digital IIR filters than the existing GA-based method reported recently in the literature.

  • tuning the structure and parameters of a neural network by using hybrid taguchi genetic algorithm
    IEEE Transactions on Neural Networks, 2006
    Co-Authors: Jinntsong Tsai, Jyhhorng Chou
    Abstract:

    In this paper, a hybrid Taguchi-genetic algorithm (HTGA) is applied to solve the problem of tuning both network structure and parameters of a feedforward neural network. The HTGA approach is a method of combining the traditional genetic algorithm (TGA), which has a powerful global exploration capability, with the Taguchi method, which can exploit the optimum offspring. The Taguchi method is inserted between crossover and mutation operations of a TGA. Then, the systematic reasoning ability of the Taguchi method is incorporated in the crossover operations to select the better genes to achieve crossover, and consequently enhance the genetic algorithms. Therefore, the HTGA approach can be more robust, statistically sound, and quickly convergent. First, the authors evaluate the performance of the presented HTGA approach by studying some global numerical optimization problems. Then, the presented HTGA approach is effectively applied to solve three examples on forecasting the sunspot numbers, tuning the associative memory, and solving the XOR problem. The numbers of hidden nodes and the links of the feedforward neural network are chosen by increasing them from small numbers until the learning performance is good enough. As a result, a partially connected feedforward neural network can be obtained after tuning. This implies that the cost of implementation of the neural network can be reduced. In these studied problems of tuning both network structure and parameters of a feedforward neural network, there are many parameters and numerous local optima so that these studied problems are challenging enough for evaluating the performances of any proposed GA-based approaches. The computational experiments show that the presented HTGA approach can obtain better results than the existing method reported recently in the literature.

  • hybrid taguchi genetic algorithm for global numerical optimization
    IEEE Transactions on Evolutionary Computation, 2004
    Co-Authors: Jinntsong Tsai, Jyhhorng Chou
    Abstract:

    In this paper, a hybrid Taguchi-genetic algorithm (HTGA) is proposed to solve global numerical optimization problems with continuous variables. The HTGA combines the traditional genetic algorithm (TGA), which has a powerful global exploration capability, with the Taguchi method, which can exploit the optimum offspring. The Taguchi method is inserted between crossover and mutation operations of a TGA. Then, the systematic reasoning ability of the Taguchi method is incorporated in the crossover operations to select the better genes to achieve crossover, and consequently, enhance the genetic algorithm. Therefore, the HTGA can be more robust, statistically sound, and quickly convergent. The proposed HTGA is effectively applied to solve 15 benchmark problems of global optimization with 30 or 100 dimensions and very large numbers of local minima. The computational experiments show that the proposed HTGA not only can find optimal or close-to-optimal solutions but also can obtain both better and more robust results than the existing algorithm reported recently in the literature.

Jinntsong Tsai - One of the best experts on this subject based on the ideXlab platform.

  • optimal design of digital iir filters by using hybrid taguchi genetic algorithm
    IEEE Transactions on Industrial Electronics, 2006
    Co-Authors: Jinntsong Tsai, Jyhhorng Chou, Tungkuan Liu
    Abstract:

    A hybrid Taguchi genetic algorithm (HTGA) is applied in this paper to solve the problem of designing optimal digital infinite-impulse response (IIR) filters. The HTGA approach is a method of combining the traditional GA (TGA), which has a powerful global exploration capability, with the Taguchi method, which can exploit the optimum offspring. The Taguchi method is inserted between crossover and mutation operations of a TGA. Based on minimizing the L/sub p/-norm approximation error and minimizing the ripple magnitudes of both passband and stopband, a multicriterion combination is employed as the design criterion to obtain the optimal IIR filter that can fit different performance requirements. The proposed HTGA approach is effectively applied to solve the multiparameter and multicriterion optimization problems of designing the digital low-pass (LP), high-pass (HP), bandpass (BP), and bandstop (BS) filters. In these studied problems, there are many parameters and numerous local optima so that these studied problems are challenging enough for evaluating the performances of any proposed GA-based approaches. The computational experiments show that the proposed HTGA approach can obtain better digital IIR filters than the existing GA-based method reported recently in the literature.

  • tuning the structure and parameters of a neural network by using hybrid taguchi genetic algorithm
    IEEE Transactions on Neural Networks, 2006
    Co-Authors: Jinntsong Tsai, Jyhhorng Chou
    Abstract:

    In this paper, a hybrid Taguchi-genetic algorithm (HTGA) is applied to solve the problem of tuning both network structure and parameters of a feedforward neural network. The HTGA approach is a method of combining the traditional genetic algorithm (TGA), which has a powerful global exploration capability, with the Taguchi method, which can exploit the optimum offspring. The Taguchi method is inserted between crossover and mutation operations of a TGA. Then, the systematic reasoning ability of the Taguchi method is incorporated in the crossover operations to select the better genes to achieve crossover, and consequently enhance the genetic algorithms. Therefore, the HTGA approach can be more robust, statistically sound, and quickly convergent. First, the authors evaluate the performance of the presented HTGA approach by studying some global numerical optimization problems. Then, the presented HTGA approach is effectively applied to solve three examples on forecasting the sunspot numbers, tuning the associative memory, and solving the XOR problem. The numbers of hidden nodes and the links of the feedforward neural network are chosen by increasing them from small numbers until the learning performance is good enough. As a result, a partially connected feedforward neural network can be obtained after tuning. This implies that the cost of implementation of the neural network can be reduced. In these studied problems of tuning both network structure and parameters of a feedforward neural network, there are many parameters and numerous local optima so that these studied problems are challenging enough for evaluating the performances of any proposed GA-based approaches. The computational experiments show that the presented HTGA approach can obtain better results than the existing method reported recently in the literature.

  • hybrid taguchi genetic algorithm for global numerical optimization
    IEEE Transactions on Evolutionary Computation, 2004
    Co-Authors: Jinntsong Tsai, Jyhhorng Chou
    Abstract:

    In this paper, a hybrid Taguchi-genetic algorithm (HTGA) is proposed to solve global numerical optimization problems with continuous variables. The HTGA combines the traditional genetic algorithm (TGA), which has a powerful global exploration capability, with the Taguchi method, which can exploit the optimum offspring. The Taguchi method is inserted between crossover and mutation operations of a TGA. Then, the systematic reasoning ability of the Taguchi method is incorporated in the crossover operations to select the better genes to achieve crossover, and consequently, enhance the genetic algorithm. Therefore, the HTGA can be more robust, statistically sound, and quickly convergent. The proposed HTGA is effectively applied to solve 15 benchmark problems of global optimization with 30 or 100 dimensions and very large numbers of local minima. The computational experiments show that the proposed HTGA not only can find optimal or close-to-optimal solutions but also can obtain both better and more robust results than the existing algorithm reported recently in the literature.

Elisabeth Olhager - One of the best experts on this subject based on the ideXlab platform.

  • body composition and growth in full term small for gestational age and large for gestational age swedish infants assessed with air displacement plethysmography at birth and at 3 4 months of age
    PLOS ONE, 2019
    Co-Authors: Anna Larsson, Peter Ottosson, Caroline Tornqvist, Elisabeth Olhager
    Abstract:

    Background Being born small for gestational age (SGA) or large for gestational age (LGA) has short and long term metabolic consequences. There is a growing interest in the extent to which body composition, both in the short and the long term, differs in infants born at the extremes of these birth weights. Methods Body composition in 25 SGA and 25 LGA infants were assessed during the first days of life and at 3–4 months of age using air displacement plethysmography. Results SGA infants had significantly lower body fat (%) at birth compared to LGA infants. SGA infants increased their body weight and length at a significantly higher rate between birth and 3–4 months than LGA infants. Fat mass (g) in SGA infants increased 23 times between birth and 3–4 months of age compared to 2.8 times for LGA infants. At 3–4 months of age LGA infants reached a threshold in body fat (%) while SGA infants were still gaining body fat (%). Conclusion Several significant differences have been identified between SGA and LGA infants, indicating that the effects of intrauterine life continues to play an important role in body composition and growth during the first 3–4 months of life. (Less)

  • body composition and growth in full term small for gestational age and large for gestational age swedish infants assessed with air displacement plethysmography at birth and at 3 4 months of age
    bioRxiv, 2018
    Co-Authors: Elisabeth Olhager, Anna Larsson, Peter Ottosson, Caroline Tornqvist
    Abstract:

    Background: Being born small for gestational age (SGA) or large for gestational age (LGA) has short and long term metabolic consequences. There is a growing interest in the extent to which body composition, both in the short and the long term, differs in infants born at the extremes of these birth weights. Methods: Body composition in 25 SGA and 25 LGA infants were assessed during the first days of life and at 3-4 months of age using air displacement plethysmography. Results: SGA infants had significantly lower body fat (%) at birth compared to LGA infants. SGA infants increased their body weight and length at a significantly higher rate between birth and 3-4 months than LGA infants. Fat mass (g) in SGA infants increased 23 times between birth and 3-4 months of age compared to 2.8 times for LGA infants. At 3-4 months of age LGA infants reached a threshold in body fat (%) while SGA infants were still gaining body fat (%). Conclusion: Several significant differences have been identified between SGA and LGA infants, indicating that the effects of intrauterine life continues to play an important role in body composition and growth during the first 3-4 months of life.

Dolores M Gomezroig - One of the best experts on this subject based on the ideXlab platform.

  • aortic intima media thickness and aortic diameter in small for gestational age and growth restricted fetuses
    PLOS ONE, 2015
    Co-Authors: Dolores M Gomezroig, Laura Guirado, Mireia Fernandezarias, Edurne Mazarico, Esther Valladares, Antonio Vela
    Abstract:

    Abstract OBJECTIVE: The objective of this study is to measure aortic intima-media thickness (aIMT) and aortic diameter (AD) in appropriate for gestational age (AGA) fetuses, small for gestational age (SGA) fetuses, and intrauterine growth restricted (IUGR) fetuses. METHODS: Case-control study performed between June 2011 and June 2012. Forty-nine AGA fetuses, 40 SGA fetuses, and 35 IUGR fetuses underwent concomitant measurement of aIMT and AD at a mean gestational age of 34.4 weeks. RESULTS: Median aIMT was higher in fetuses with IUGR (0.504 mm [95%CI: 0.477-0.530 mm]), than in SGA fetuses (0.466 mm [95% CI: 0.447-0.485 mm]), and AGA fetuses (0.471 mm [95% CI: 0.454-0.488 mm]) (p = 0.023). Mean AD was significantly lower in fetuses with IUGR (4.451 mm [95% CI: 4.258-4.655 mm]), than in AGA fetuses (4.74 mm [95% CI: 4.63-4.843 mm]) (p = 0.028). CONCLUSIONS: Growth restricted fetuses have a thicker aortic wall than AGA and SGA fetuses, which possibly represents preclinical atherosclerosis and a predisposition to later cardiovascular disease.

  • aortic intima media thickness and aortic diameter in small for gestational age and growth restricted fetuses
    PLOS ONE, 2015
    Co-Authors: Dolores M Gomezroig, Laura Guirado, Mireia Fernandezarias, Edurne Mazarico, Esther Valladares, Antonio Vela
    Abstract:

    Abstract OBJECTIVE: The objective of this study is to measure aortic intima-media thickness (aIMT) and aortic diameter (AD) in appropriate for gestational age (AGA) fetuses, small for gestational age (SGA) fetuses, and intrauterine growth restricted (IUGR) fetuses. METHODS: Case-control study performed between June 2011 and June 2012. Forty-nine AGA fetuses, 40 SGA fetuses, and 35 IUGR fetuses underwent concomitant measurement of aIMT and AD at a mean gestational age of 34.4 weeks. RESULTS: Median aIMT was higher in fetuses with IUGR (0.504 mm [95%CI: 0.477-0.530 mm]), than in SGA fetuses (0.466 mm [95% CI: 0.447-0.485 mm]), and AGA fetuses (0.471 mm [95% CI: 0.454-0.488 mm]) (p = 0.023). Mean AD was significantly lower in fetuses with IUGR (4.451 mm [95% CI: 4.258-4.655 mm]), than in AGA fetuses (4.74 mm [95% CI: 4.63-4.843 mm]) (p = 0.028). CONCLUSIONS: Growth restricted fetuses have a thicker aortic wall than AGA and SGA fetuses, which possibly represents preclinical atherosclerosis and a predisposition to later cardiovascular disease.