Palynological studies of family Euphorbiaceae from kaghan valley, Mansehra, N.W.F.P., Pakistan

Palynological study of 04 species belonging to 04 genera of the family Euphorbiaceae from Kaghan Valley was conducted. Pollen grains of Euphorbiaceae are suboblate to prolate or prolate spheroidal to subprolate, 3-colporate, amb circular, circular-lobate or inter-subangular, colpi varying in length, in width and in thickness of margin, ora mostly not crassimarginate, transversally parallel, but some of them, ora transversally elliptic or circular, rarely crassimarginate, exine 1-3 micro m thick, tectum psilate or with scabrate, verrucate, gemmate or baculate processes, sexine mostly granulate or finely reticulate, with OL- or croton-pattern, nexine as thick as sexine. Size of grain varies from 15 to 60 micro m

Palynological and ethnobotanical studies of Genus Pinus from Hazara, N.W.F.P., Pakistan

Pollen morphology of genus Pinuss growing wild in Hazara, N.W, F.P., Pakistan was studied. Grains were vesiculate, exine 3-4 micro thick, sexilte reticulate. Size of the grain varies from 36 x 54 [53 x 73.8]64 x 96 micro m to 40 x 614 [47.2 x 75]567 x 88.3 micro m

Prediction of anoxic sulfide biooxidation under various HRTs using artificial neural networks / 生物医学与环境科学（英文）

<p><b>OBJECTIVE</b>During present investigation the data of a laboratory-scale anoxic sulfide oxidizing (ASO) reactor were used in a neural network system to predict its performance.</p><p><b>METHODS</b>Five uncorrelated components of the influent wastewater were used as the artificial neural network model input to predict the output of the effluent using back-propagation and general regression algorithms. The best prediction performance is achieved when the data are preprocessed using principal components analysis (PCA) before they are fed to a back propagated neural network.</p><p><b>RESULTS</b>Within the range of experimental conditions tested, it was concluded that the ANN model gave predictable results for nitrite removal from wastewater through ASO process. The model did not predict the formation of sulfate to an acceptable manner.</p><p><b>CONCLUSION</b>Apart from experimentation, ANN model can help to simulate the results of such experiments in finding the best optimal choice for ASObased denitrification. Together with wastewater collection and the use of improved treatment systems and new technologies, better control of wastewater treatment plant (WTP) can lead to more effective maneuvers by its operators and, as a consequence, better effluent quality.</p>

Anatomical studies on water hyacinth (Eichhornia crassipes (Mart.) Solms) under the influence of textile wastewater / 浙江大学学报（英文版）（B辑：生物医学和生物技术）

Water hyacinth (Eichhornia crassipes (Mart.) Solms) is a prolific free floating aquatic macrohpyte found in tropical and subtropical parts of the earth. The effects of pollutants from textile wastewater on the anatomy of the plant were studied. Water hyacinth exhibits hydrophytic adaptations which include reduced epidermis cells lacking cuticle in most cases, presence of large air spaces (7 approximately 50 microm), reduced vascular tissue and absorbing structures. Textile waste significantly affected the size of root cells. The presence of raphide crystals was noted in parenchyma cells of various organs in treated plants.