Hydrological analysis as a technical tool to support strategic and economic development: A case study of Lake Navaisha,Kenya

Effective integrated water resources management requires reliable estimation of an overall basin water budget and of hydrologic fluctuations between groundwater and surface‐water resources. Seasonal variability of groundwater‐surface water exchange fluxes impacts on the water balance. The long term lake water balance was calculated by Modflow using the stage‐volume rating curve of Lake Package LAK3. The long term average storage volume change is 8.4 × 10⁸ m³/month. The lake water balances suggests that the lake is not in equilibrium with the inflow and outflow terms. Using field abstraction data analysis and model simulation, the combined volume of lake‐groundwater used for industrial abstraction since the last three decades was estimated. This requires an average abstraction amount of 7.0 × 10⁶ m³/month with a long term trend of abstraction ratio 30% (groundwater) and 70% (lake water) since 1980. The amount resulted in a lake which might have been 4.8 m higher than was observed in the last stress period (2010). A long term regional groundwater budget is calculated reflecting all water flow in to and out of the regional aquifer. The model water balance suggests that lake Navaisha basin is in equilibrium with a net outflow about 1% greater than the inflow over the calibrated period of time (1932–2010). The regional model is best used for broad‐scale predictions and can be used to provide a general sense of groundwater to surface water and groundwater to groundwater impacts in the basin. A basin wide water resource management strategy can be designed by integrating the lake/wetland within the regional groundwater model to increase the level of sustainable production and good stewardship in Lake Navaisha. Such hydrological analysis is crucial in making the model serve as simulator of the response of lake stage to hydraulic stresses applied to the aquifer and variation in climatic condition.     

Comparative study of hydrocarbon, fluorocarbon, and aromatic bonded RP-HPLC stationary phases by linear solvation energy relationships.

The retention properties of eight alkyl, aromatic, and fluorinated reversed-phase high-performance liquid chromatography bonded phases were characterized through the use of linear solvation energy relationships (LSERs). The stationary phases were investigated in a series of methanol/water mobile phases. LSER results show that solute molecular size and hydrogen bond acceptor basicity under all conditions are the two dominant retention controlling factors and that these two factors are linearly correlated when either different stationary phases at a fixed mobile-phase composition or different mobile-phase compositions at a fixed stationary phase are considered. The large variation in the dependence of retention on solute molecular volume as only the stationary phase is changed indicates that the dispersive interactions between nonpolar solutes and the stationary phase are quite significant relative to the energy of the mobile-phase cavity formation process. PCA results indicate that one PCA factor is required to explain the data when stationary phases of the same chemical nature (alkyl, aromatic, and fluoroalkyl phases) are individually considered. However, three PCA factors are not quite sufficient to explain the whole data set for the three classes of stationary phases. Despite this, the average standard deviation obtained by the use of these principal component factors are significantly smaller than the average standard deviation obtained by the LSER approach. In addition, selectivities predicted through the LSER equation are not in complete agreement with experimental results. These results show that the LSER model does not properly account for all molecular interactions involved in RP-HPLC. The failure could reside in the V2 solute parameter used to account for both dispersive and cohesive interactions since "shape selectivity" predictions for a pair of structural isomers are very bad.     

The Influence of Large Scale Phosphate Mining on the Water Quality of the Huangbaihe River Basin in China: Dominant Pollutants and Spatial Distributions

Large scale phosphate mining in the Huangbaihe River Basin, China has reduced the self-purification capacity of the basin’s fresh water. Three years (2014–2016) of monitoring data and chemometric analysis were used to identify the dominant pollutants and define their spatial distribution in the basin. Principal component analysis was applied to determine the contribution of the individual pollutants. Total phosphorus (TP) 53%, water temperature (TEMP) 27%, and total nitrogen (TN) 20% proved to be the dominant problems. A discriminant functions (DF) model was developed to classify the study area into high, moderate, and low pollution zones. The DF coefficients were applied to analyze the correlation between DF and the measured parameters and it was found that TP, TN, and TEMP were positively correlated with the DF, indicating that these parameters were the most important. Finally, the results were compared with the locations of the mining activities, which revealed that TP is higher in the upper sub-basins, Xuanmiaoguan and Tianfumiao, where most of the high pollution zones are located and more than 78% of the areas are affected by the phosphate mines. It is concluded that the phosphate mining is the major source of pollution and TP is the dominant pollutant responsible for the total water quality variation in the river basin. More effective management measures have to be taken to reduce phosphorus runoff into the reservoir watersheds.

     

Polyphenol input to the antioxidant activity of yerba mate (Ilex paraguariensis) extracts

Industrial processing modified the polyphenol content, composition and antioxidant activity of the yerba mate extracts. Pre-dried leaves were the most appropriate raw material combining maximum activity with high polyphenol content. Chlorogenic acid and its derivatives were the major components of the phenolic fraction but we also identified caffeic, rutin and quercetin.Yerba mate extracts inhibited malonedialdehyde formation in sunflower oil (20 μmol/kg) and conjugated dienes production in oil/water emulsions (60 μmol/kg). Enhancing the dose to 60 μmol/kg reduced 27.8% the extract’s activity in oil.The relationship between polyphenol composition and antioxidant activity of a mixture of caffeic, chlorogenic, kaempferol, quercetin and rutin was satisfactorily predicted with a polynomial model. Results showed that quercetin was the highest contributor to the linear term followed by kaempferol and caffeic acid while rutin and chlorogenic acid inputs were the lowest. The model detected five synergistic and six antagonistic effects.     

Conspecific urine markings in male rats (Rattus norvegicus) selected for relative aggressiveness.

Male laboratory rats were selected for relative aggressiveness and tested individually and in pairs to examine conspecific marking in relation to object marking. Urine deposited on the other animal and in the environment was rendered visible and quantifiable with sodium fluorescein and filter paper, respectively. Moderately aggressive males were used in Experiment 1, and despite individual differences in both forms of marking, there was a high positive correlation between quantity of marks in the environment and on a conspecific. In Experiment 2, aggressive males marked the environment and their nonaggressive partners more than vice versa. Nonaggressive males were paired successfully with an aggressive and another nonaggressive male in Experiment 3 to examine the crawl-over response, the behavior used by rats to deposit scents on another rat. Nonaggressive males deposited more urine with each crawl over an aggressive than over a nonaggressive male, but they crawled over the nonaggressive male more often than the aggressive male. These data are interpreted as suggesting that conspecific marking is modified by limitations imposed on the behavior by the social relation of the interacting animals. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Handover Performance Evaluation Under Dynamic User Characteristics

Mobile robot navigation is an obscure condition that plays a vital role in different applications such as military purposes, navy, etc. now a day's lot of problems occur during navigation. To solve the navigation problem an RGB-Depth sensor along with support value-based neuro-fuzzy sliding mode controller techniques (SVB-NFSMC) are proposed. The RGB-Depth sensor is used to estimate the depth map using the linear coefficients along with the bilateral filter. Then the angular and linear velocity is calculated to define the angular position and the object movement. Then the calculation of support value is based on the above angular and linear estimation values. Here the depth map and support value as a training data set input are given to the controller. Subsequently, the sliding mode controller provides the guiding commands in terms of guidance law, control law to the robot system. The ANFIS and the GWO algorithm are used to optimize the parameters is given to the controller then the Lyapunov function is used to analyze the stability of the system. Finally, compare the proposed work with the existing AKH-NFIS and the other SMC methods provides better outcomes.