A Highly Efficient Gene Expression Programming Model for Predicting the Discharge Coefficient in a Side Weir along a Trapezoidal Canal

Abstract Discharge coefficients (C0) for ogee weirs are essential factors for predicting the discharge-head relationship. The present study investigates three influences on the C0: effect of approach depth, weir upstream face slope, and the actual head, which may differ from the design head. This study uses experimental data with multiple non-linear regression techniques and Gene Expression Programming (GEP) models that are applied to introduce practical equations that can be used for design. Results show that the GEP method is superior to the regression analysis for predicting the discharge coefficient. Performance criteria for GEP are R2 = 0.995, RMSE = 0.021 and MAE = 0.015. Design examples are presented that show that the proposed GEP equation correlates well with the data and eliminates linear interpolation using existing graphs.

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A Simple, Rapid, and Highly Efficient Gene Expression System for Multiheme Cytochromes c

Bioscience Biotechnology and Biochemistry ◽

10.1271/bbb.65.185 ◽

2001 ◽

Vol 65 (1) ◽

pp. 185-189 ◽

Cited By ~ 25

Author(s):

Kiyoshi OZAWA ◽

Fumiko YASUKAWA ◽

Yumiko FUJIWARA ◽

Hideo AKUTSU

Keyword(s):

Gene Expression ◽

Expression System ◽

Gene Expression System ◽

Highly Efficient ◽

Efficient Gene ◽

Cytochromes C

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Local Gene Delivery System by Bubble Liposomes and Ultrasound Exposure into Joint Synovium

Journal of Drug Delivery ◽

10.1155/2011/203986 ◽

2011 ◽

Vol 2011 ◽

pp. 1-7 ◽

Cited By ~ 13

Author(s):

Yoichi Negishi ◽

Yuka Tsunoda ◽

Yoko Endo-Takahashi ◽

Yusuke Oda ◽

Ryo Suzuki ◽

...

Keyword(s):

Gene Expression ◽

Gene Transfer ◽

Gene Delivery ◽

Delivery System ◽

Imaging System ◽

Effective Means ◽

Gene Delivery System ◽

Highly Efficient ◽

Efficient Gene

Recently, we have developed novel polyethylene glycol modified liposomes (bubble liposomes; BL) entrapping an ultrasound (US) imaging gas, which can work as a gene delivery tool with US exposure. In this study, we investigated the usefulness of US-mediated gene transfer systems with BL into synoviocytes in vitro and joint synovium in vivo. Highly efficient gene transfer could be achieved in the cultured primary synoviocytes transfected with the combination of BL and US exposure, compared to treatment with plasmid DNA (pDNA) alone, pDNA plus BL, or pDNA plus US. When BL was injected into the knee joints of mice, and US exposure was applied transcutaneously to the injection site, highly efficient gene expression could be observed in the knee joint transfected with the combination of BL and US exposure, compared to treatment with pDNA alone, pDNA plus BL, or pDNA plus US. The localized and prolonged gene expression was also shown by an in vivo luciferase imaging system. Thus, this local gene delivery system into joint synovium using the combination of BL and US exposure may be an effective means for gene therapy in joint disorders.

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Prediction of Discharge Capacity of Labyrinth Weir with Gene Expression Programming

10.20944/preprints202001.0313.v1 ◽

2020 ◽

Author(s):

Hossein Bonakdari ◽

Isa Ebtehaj ◽

Bahram Gharabaghi ◽

Ali Sharifi ◽

Amir Mosavi

Keyword(s):

Gene Expression ◽

Relative Error ◽

Discharge Coefficient ◽

Gene Expression Programming ◽

Vertex Angle ◽

Dimensionless Parameters ◽

Labyrinth Weir ◽

Predicted Values ◽

Crest Length ◽

Labyrinth Weirs

This paper proposes a model based on gene expression programming for predicting discharge coefficient of triangular labyrinth weirs. The parameters influencing discharge coefficient prediction were first examined and presented as crest height ratio to the head over the crest of the weir (p/y), crest length of water to channel width (L/W), crest length of water to the head over the crest of the weir (L/y), Froude number (F=V/√(gy)) and vertex angle () dimensionless parameters. Different models were then presented using sensitivity analysis in order to examine each of the dimensionless parameters presented in this study. In addition, an equation was presented through the use of nonlinear regression (NLR) for the purpose of comparison with GEP. The results of the studies conducted by using different statistical indexes indicated that GEP is more capable than NLR. This is to the extent that GEP predicts the discharge coefficient with an average relative error of approximately 2.5% in such a manner that the predicted values have less than 5% relative error in the worst model.

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