Evolutionary algorithm for water storage forecasting response to climate change with small data sets: The Wolonghu Wetland, China

A novel genetic programming (GP) technique, a new method of evolutionary algorithms, was applied to a small data set to predict the water storage of Wolonghu wetland in response to the climate change in the northeastern part of China. Fourteen years (1993-2006) of annual water storage and climatic data of the wetland were used for model training and testing. Results of simulations and predictions illustrate a good fit between calculated water storage and observed values (mean absolute percent error = 9.47, r = 0.99). By comparison, a multilayer perceptron method (a popular artificial neural network model) and Grey theory model with the same data set were applied for performance estimation. It was found that GP technique had better performance than the other two methods, in both the simulation step and the predicting phase. The case study confirms that GP method is a promising way for wetland managers to make a quick estimation of fluctuations of water storage in some wetlands under the limitation of a small data set

Evolutionary modeling for streamflow forecasting with minimal datasets: a case study in the West Malian River, China

A large data set is generally needed when modeling hydrological processes. However, for developing countries such as China, data sets are often unavailable in remote areas. An attempt to apply a novel genetic programming (GP) technique was made to model the relationship between streamflow of the West Malian River and the impact of climate change in the northeastern part of China. Available annual streamflow and climatic data were used for training and testing of the GP model. Data from the years between 1982 and 2002 were used for automatic selection of the model relationship. Prediction of the model was undertaken for the period 2003–2006 and the results were compared with measured data. Predicted annual streamflow of the West Malian River agreed with measured data to an acceptable degree of accuracy even with a small amount of data set. For comparison, a multilayer perceptron method with back propagation algorithm, a gray theory model, and a multiple linear regression model were selected to conduct the prediction with the same data set. Results showed that the performance of GP method was generally better than other statistical methods such as multilayer perceptron, gray theory model, and multiple linear regression model. Further, the results also showed that the GP method is a useful tool for water resource management, especially in developing countries, to evaluate the potential impacts of climate change on the streamflow when large data sets are unavailable

Axial Compressive Behavior of Glass Fiber-Reinforced Hollow Concrete Columns

To investigate the axial compression behavior of glass fiber-reinforced polymer tubes filled with reinforced hollow concrete members, the finite element model was established in ABAQUS. The correctness of the finite element model was verified by comparing the simulation results with the existing test results. On this basis, the influence of the main parameters such as GFRP tube wall thickness, filament winding angle, concrete strength grade, and hollow ratio on the axial compression behavior was analyzed. The calculation formula of the bearing capacity under axial compression of the GFRP tube filled with reinforced hollow concrete members was established. The results show that the load and strain curves and failure modes of the model and the established bearing capacity formula are in good agreement with the test results. The axial compression capacity of the hollow members increases with the increase in the thickness of GFRP tube wall thickness, filament winding angle, and concrete strength grade and decreases with the increase in the hollow ratio. The GFRP tube filament winding angle and hollow ratio have significant influence on the bearing capacity of axial compression, followed by the GFRP tube wall thickness and concrete strength grade. The radius ratio of hollow part should be 0.250.5. The axial compression bearing capacity of the hollow members can be compensated by properly increasing the GFRP tube wall thickness, filament winding angle, or concrete strength grade. The research conclusion can provide some reference for the design of the structure

Lyoniresinol 3α-O-β-D-glucopyranoside-mediated hypoglycaemia and its influence on apoptosis-regulatory protein expression in the injured kidneys of streptozotocin-induced mice.

Averrhoa carambola L. (Oxalidaceae) root (ACLR) has a long history of use in traditional Chinese medicine for treating diabetes and diabetic nephropathy (DN). (±)-Lyoniresinol 3α-O-β-D-glucopyranoside (LGP1, LGP2) were two chiral lignan glucosides that were isolated from the ACLR. The purpose of this study was to investigate the effect of LGP1 and LGP2-mediated hypoglycaemia on renal injury in streptozotocin (STZ)-induced diabetic mice. STZ-induced diabetic mice were administrated LGP1 and LGP2 orally (20, 40, 80 mg/kg body weight/d) for 14 days. Hyperglycaemia and the expression of related proteins such as nuclear factor-κB (NF-κB), caspase-3, -8, -9, and Bcl-associated X protein (Bax) were markedly decreased by LGP1 treatment. However, LGP2 treatment had no hypoglycaemic activity. Diabetes-dependent alterations in the kidney such as glomerular hypertrophy, excessive extracellular matrix amassing, and glomerular and tubular basement membrane thickening were improved after 14 days of LGP1 treatment. B cell lymphoma Leukaemia-2 (Bcl-2) expression was reduced in the STZ-induced diabetic mouse kidneys but was enhanced by LGP1 treatment. These findings suggest that LGP1 treatment may inhibit diabetic nephropathy progression and may regulate several pharmacological targets for treating or preventing diabetic nephropathy

Effect of the Total Extract of Averrhoacarambola (Oxalidaceae) Root on the Expression Levels of TLR4 and NF-κB in Streptozotocin-Induced Diabetic Mice

Background: Averrhoacarambola L., which is a folk medicine used in diabetes mellitus (DM) in ancient China, has been reported to have anti-diabetic efficacy. Aims: The aim of this study was to evaluate the hypoglycemic effect of the extract of Averrhoacarambola L. root (EACR) on the regulation of the Toll-like receptor 4 (TLR4)-Nuclear-factor kappa B (NF-κB) pathway in B) pathway in streptozotocin (STZ)-induced diabetic mice. Methods: the mice were injected with STZ (120 mg/kg body weight) via a tail vein. After 72 h, the mice with FBG = 11.1 mmol/L were confirmed as having diabetes. Subsequently, the mice were treated intragastrically with EACR (300, 600, 1200 mg/kg body weight/d) and metformin (320 mg/kg body weight/d) for 14 days. Results: As a result the serum fasting blood glucose (FBG), interleukin-6 (IL-6) and tumor necrosis factor-a (TNF-a) levels were decreased following EACR administration. Immunohistochemical analysis revealed that the pancreatic tissue expression levels of TLR4 and NF-κB were downregulated after EACR administration. EACR suppressed pancreatic mRNA expression level of TLR4 and blocked the downstream NF-κB pathway in the pancreas. According to Western blot analysis EACR suppressed pancreatic TLR4 and NF-κB protein expression levels. Histopathological examination of the pancreas showed that STZ-induced pancreas lesions were alleviated by the EACR treatment. Conclusion: These findings suggest that the modulation of the IL-6 and TNF-a inflammatory cytokines and the suppression of the TLR4-NF-κB pathway are most likely involved in the anti-hyperglycemic effect of EACR in STZ-induced diabetic mice

Phenolic and Lignan Glycosides from the Butanol Extract of Averrhoa carambola L. Root

Fifteen compounds, which included six chiral lignans and nine phenolic glycosides, were separated from the butanol fraction of Averrhoa carambola L. root and identified. All of the compounds, namely 3,4,5-trimethoxyphenol-1-O-β-D-glucopyranoside (1), benzyl-1-O-β-D-glucopyranoside (2), (+)-5'-methoxyisolariciresinol 3α-O-β-D-gluco-pyranoside (3), (+)-isolariciresinol 3α-O-β-D-glucopyranoside (4), koaburaside (5), (+)-lyoniresinol 3α-O-β-D-glucopyranoside (6), (−)-lyoniresinol 3α-O-β-D-glucopyranoside (7), (−)-5'-methoxyisolariciresinol 3α-O-β-D-glucopyranoside (8), (−)-isolariciresinol 3α-O-β-D-glucopyranoside (9), 3,5-dimethoxy-4-hydroxyphenyl 1-O-β-apiofuranosyl (1''→6')-O-β-D-glucopyranoside (10), 3,4,5-trimethoxyphenyl 1-O-β-apiofuranosyl (1''→6')-β-gluco-pyranoside (11), methoxyhydroquinone-4-β-D-glucopyranoside (12), (2S)-2-O-β-D-gluco-pyranosyl-2-hydroxyphenylacetic acid (13), 3-hydroxy-4-methoxyphenol 1-O-β-D-apio-furanosyl-(1''→6')-O-β-D-glucopyranoside (14) and 4-hydroxy-3-methoxyphenol 1-O-β-D-apiofuranosyl-(1''→6')-O-β-D-glucopyranoside (15) were isolated from this plant for the first time