RAPD PCR Confirms Absence of Genetic Variation Between Insecticide Resistant Variants of the Green Peach Aphid, \u3ci\u3eMyzus Persicae\u3c/i\u3e (Homoptera: Aphididae)

Previous allozyme analysis has revealed an apparent absence of enzyme variability in the green peach aphid, Myzus persicae (Sulzer). We are interested in determining the genetic relatedness of individual M persicae clones carrying different numbers of esterase 4 (E4) gene copies conferring resistance to insecticides, in order to determine how many times and in what geographic locations resistance via gene duplication may have evolved. We have therefore extended the analysis of genetic variability in M. persicae to the DNA level using random amplification of polymorphic DNA (RAPD) with single 10 mer oligonucleotide primers. Here we report a lack of variability be- tween resistant clones in Wisconsin populations even at the DNA level Further, \u27fast\u27 E4 (FE4) variants appear to be absent from Wisconsin populations, despite FE4 variants of moderate resistance (Rl) being the most common clones in the United Kingdom. These results suggest that resistance in M. persicae may have evolved a very few times and that North American populations may differ from those in Europe by founder effects

A Comparative Study of Adaptive Neuro Fuzzy Inference System and Artificial Neural Networks for Predicting Groundwater Hydraulic Head in an Arid Region

يهدف هذا البحث إلى تطوير نموذج تنبؤي لتقدير منسوب المياه الجوفية في منطقة سفوان-الزبير باستخدام نظام الاستدلال العصبي الضبابي المكيف (ANFIS). تمثل هذه المنطقة الجزء الجنوبي من الصحراء العراقية، وهي منطقة قاحلة ذات موارد مائية محدودة. تم توليد البيانات المطلوبة لبناء نموذج ANFIS باستخدام نموذج MODFLOW V.5.3)). حيث تمت معايرة نموذج MODFLOW اعتمادا على القياسات الحقلية خلال سنة واحدة. ولد نموذج MODFLOW (3797) قيمة للمنسوب الهيدروليكي خلال كل شهر. استخدمت 70 ٪ من هذه القيم (2658 عينة) للتدريب، و30 ٪ منها (1139 عينة) في عملية التحقق. تم مقارنة دقة نماذج ANFIS مع دراسة سابقة معتمدة على تقنية الشبكة العصبية الاصطناعية (ANN). كانت متغيرات الادخال من المناسيب الهيدروليكية المتعاقبة ومعدلات تغذية المياه الجوفية. لا توجد زيادة كبيرة في دقة التقدير عند إضافة متغير إدخال آخر (معدل تغذية المياه الجوفية)، لأن مقدار هذا المتغير قليل جدًا، لذلك كان تأثيره على النتائج غير محسوس. توضح مقارنة ANFIS وANN أن نموذج ANFIS هو أفضل من ANN في مرحلة التحقق. يمكن ان يعزا ذلك الى ان نموذج ANFIS يجمع بين أساسيات المنطق الضبابي والشبكات العصبية؛ وبالتالي يمكن استخدام خصائصها في إطار واحد. يمكن استنتاج أن نموذج ANFIS أكثر ملائمة من نموذج ANN للتنبؤ بالمنسوب الهيدروليكي للمياه الجوفية من بيانات المدخلات ذات الصلة.The aim of this research is to develop a predictive model to estimate the groundwater head in Safwan-Zubair area by using an adaptive neural fuzzy inference system (ANFIS). This area represents the southern sector of the Iraqi Desert, an arid region with scarce and limited resources. The data required for building the ANFIS model are generated using MODFLOW model (V.5.3). MODFLOW model was calibrated based on field measurements during one year. MODFLOW model generated (3797) hydraulic head values during each month. 70% of these values (2658 samples) was used for training, 30% of these values (1139 samples) was used for checking. The accuracy of the ANFIS models are compared with previous work based on artificial neural network (ANN) technique. Different combination of successive hydraulic heads and recharge rates of groundwater is used as input variables. There is no significant increase in the estimation accuracy when adding another input variable (recharge rate). Because the amount of this variable is very little, so its influence on the results was imperceptible. A comparison of ANFIS and ANN shows that the ANFIS model performs preferable than the ANN model on the checking phase. ANFIS model combines both fuzzy logic basics and neural networks; thus their properties can be utilized in one frame. It can be concluded, the ANFIS model appears to be more convenient than the ANN model for predicting groundwater hydraulic head from related input data

Identification of Manning’s Coefficient Using HEC-RAS Model: Upstream Al-Amarah Barrage

In understanding the hydraulic characteristics of river system flow, the hydraulic simulation models are essential tools. This study submits the results of the proposition of a hydraulic model in order to determine the roughness coefficient (Manning’s coefficient n) of the Tigris River along 3.5 km within the Maysan Governorate, south of Iraq. HEC-RAS software was the simulation tool used in this study. The HEC-RAS model was adopted, calibrated, and validated in adopting two sets of observed water levels. Graphical and statistical approaches were used for model calibration and verification. Results from this investigation showed that a value of Manning’s coefficient of 0.025 gave an acceptable agreement between observed and simulated values of water levels

Nutrients Removal from Domestic Wastewater in Basrah City (Southern Iraq) using Combined A

The nutrients removal from domestic wastewater in Basrah City (Southern Iraq) by using the technology of up flow A2-O Bio Contact Oxidation with bypass flow was studied in this research. The treatment system was designed in order to treating 100 L/day of domestic wastewater by using a laboratory scale Anaerobic-Anoxic-Aerobic Moving Bed Biofilm Reactors (MBBRS) in series form with effective volume equal to 15 L, 15 L, and 30 L respectively. Kaldnes polyethylene media (K1) was used in this study in order to achieve attached biofilm process with filling ratio equal to 30% for both anaerobic anoxic MBBRS. and with filling ratio 50% for aerobic MBBR. After the biofilm was developed in the carriers the system was operated under internal recycle ratio equal to 100%. bypass ratio equal to 40%. and under 3 different external recycle ratio (25%, 50%, and 100%). The experimental results showed that the optimal value of the external recycle ratio was equal to 50 %, which the average values of removal efficiencies of COD, NH4+-N, TN and TP were equal to 98.15 %, 97.16%, 82.12%, and 93.39 % respectively. Under the condition of the optimum value of external recycle ratio the average concentration of the dissolved oxygen in both anoxic and aerobic reactors were equal to 0.151 mg/L, and 3.57 mg/L respectively, and the temperature of water wras controlled in the range of 35° C in the anaerobic reactor and in the range of 30°C in both anoxic and aerobic reactors by used temperature controlled

Nutrients Removal from Domestic Wastewater in Basrah City (Southern Iraq) using Combined A2/O Bio Contact Oxidation Technology

The nutrients removal from domestic wastewater in Basrah City (Southern Iraq) by using the technology of up flow A2-O Bio Contact Oxidation with bypass flow was studied in this research. The treatment system was designed in order to treating 100 L/day of domestic wastewater by using a laboratory scale Anaerobic-Anoxic-Aerobic Moving Bed Biofilm Reactors (MBBRS) in series form with effective volume equal to 15 L, 15 L, and 30 L respectively. Kaldnes polyethylene media (K1) was used in this study in order to achieve attached biofilm process with filling ratio equal to 30% for both anaerobic anoxic MBBRS. and with filling ratio 50% for aerobic MBBR. After the biofilm was developed in the carriers the system was operated under internal recycle ratio equal to 100%. bypass ratio equal to 40%. and under 3 different external recycle ratio (25%, 50%, and 100%). The experimental results showed that the optimal value of the external recycle ratio was equal to 50 %, which the average values of removal efficiencies of COD, NH4+-N, TN and TP were equal to 98.15 %, 97.16%, 82.12%, and 93.39 % respectively. Under the condition of the optimum value of external recycle ratio the average concentration of the dissolved oxygen in both anoxic and aerobic reactors were equal to 0.151 mg/L, and 3.57 mg/L respectively, and the temperature of water wras controlled in the range of 35° C in the anaerobic reactor and in the range of 30°C in both anoxic and aerobic reactors by used temperature controlled

Estimation of Suspended Sediment Load Using Artificial Neural Network in Khour Al Zubair Port, Iraq

The port of Khour Al-Zubair is located 60.0 km south of the city centre of Basrah; it is also located 105.0 kilometres from the northern tip of the Arabian Gulf. The main goal of this paper is to estimate the concentration of suspended deposit (SSC) in “Khour Al-Zubair” port using a Multilayer Perceptron Neural Network (MLP) based on hydraulic and local boundary parameters while also studying the effect of these parameters on estimating the SSC. Five input parameters (channel width, water depth, discharge, cross-section area, and flow velocity) are used for estimating SSC. Different input hydraulic and local boundary parameter combinations in the three sections (port center, port south, and port north) were used for creating nine models. The use of both hydraulic and local boundary parameters for SSC estimation is very important in the port area for estimating sediment loads without the need for field measurements, which require effort and time