Sustainability assessment of wastewater treatment techniques in urban areas of Iraq using multi-criteria decision analysis (MCDA)

Sustainable development is based on environmental, social, economic, and technical dimensions. In this study, the sustainability of wastewater treatment techniques in urban areas of Iraq was assessed using a multi-criteria decision analysis (MCDA)/the weighted sum model (WSM). The analysis was performed on 13 operating wastewater treatment plants in 10 provinces, Iraq, using a questionnaire sheet with the assistance of 52 specialists in the Ministry of Municipalities and Public Works, Iraq. Four types of wastewater treatment techniques (Conventional Treatment, Oxidation Ditches, Aeration Lagoons, and membrane bio-reactor (MBR)) were assessed. The environmental, social, economic, and technical dimensions were represented by 11, 5, 7, and 4 indicators, respectively. The main results of this study indicate that the sustainability of MBR recorded the highest total importance; the order of the total importance from the highest to the lowest was: MBR > Oxidation Ditches > Aeration Lagoons > Conventional Treatment. The environmental dimension proved its dominance in the four studied treatment techniques' sustainability as it recorded the maximum contribution to sustainability. While the technical dimension recorded the least contribution to sustainability, the order from the highest to the lowest was: Environmental Dimension > Economic Dimension > Social Dimension > Technical Dimension

Disambiguating the Similar: Investigating Pattern Separation in Medial Temporal Lobe Structures Using Rodent Models

This dissertation investigates the mechanisms underlying pattern separation, using rodent models and behavioural tasks that assess the use of representations for similar stimuli. Pattern separation is a theoretical mechanism involving the transformation of inputs into output representations that are less correlated to each other. Because of this orthogonalizing process, similar experiences are stored as discrete non-overlapping representations. Studying pattern separation emphasizes the important but often overlooked fact that successful memory involves more than just remembering events over a period of time, but also differentiating between similar memories. Through a series of experiments this dissertation adds support to the literature that the dentate gyrus (DG) subregion of the hippocampus is important for pattern separation when encoding spatial and contextual inputs. Using the Spontaneous Location Recognition (SLR) task it is shown the brain-derived neurotrophic factor (BDNF) can improve performance by acting via N-methyl-D-aspartate (NMDA) glutamate receptors in the DG and adult-born hippocampal neurons. Manipulating the level of neurogenesis by inhibiting Wnt signalling or by administering acyl-ghrelin systemically is shown to impair and enhance performance on SLR, respectively. Using a novel exposure paradigm in combination with SLR, it is demonstrated for the first time that the relationship between pattern separation and neurogenesis may be reciprocal, such that inhibiting neurogenesis impairs pattern separation, enhancing neurogenesis improves pattern separation, and performing pattern separation enhances the production or survival of adult-born hippocampal neurons. Finally, it is shown that the $TgTau^{P301L}$ mouse model of dementia exhibits spatial and object recognition memory impairments once aged, recapitulating a dementia-like phenotype. Understanding the mechanisms that contribute to effective pattern separation may help elucidate the processes underlying the memory impairment experienced by AD patients. This dissertation concludes with a critical discussion about whether pattern separation can be studied using behavioural paradigms.Gates Cambridge; NSERC; St. John’s Colleg

Statistical modeling of monthly streamflow using time series and artificial neural network models: Hindiya Barrage as a case study

Autoregressive Integrated Moving Average (ARIMA) Box-Jenkins models combine the autoregressive and moving average models to a stationary time series after the appropriate transformation, while the nonlinear autoregressive (N.A.R.) or the autoregressive neural network (ARNN) models are of the kind of multi-layer perceptron (M.L.P.), which compose an input layer, hidden layer and an output layer. Monthly streamflow at the downstream of the Euphrates River (Hindiya Barrage) /Iraq for the period January 2000 to December 2019 was modeled utilizing ARIMA and N.A.R. time series models. The predicted Box-Jenkins model was ARIMA (1,1,0) (0,1,1), while the predicted artificial neural network (N.A.R.) model was (M.L.P. 1-3-1). The results of the study indicate that the traditional Box-Jenkins model was more accurate than the N.A.R. model in modeling the monthly streamflow of the studied case. Performing a one-step-ahead forecast during the year 2019, the forecast accuracy between the forecasted and recorded monthly streamflow for both models was as follows: the Box-Jenkins model gave root mean squared error (RMSE = 48.7) and the coefficient of determination R2 = 0.801), while the (NAR) model gave (RMSE = 93.4) and R2 = 0.269). Future projection of the monthly stream flow through the year 2025, utilizing the Box-Jenkins model, indicated the existence of long-term periodicity

A Review of Optimization to the Operation of a Complex Water Resources System Based on Certain Practical Assumptions and Simplification

تم إعداد هذا البحث لمراجعة التشغيل الأمثل للنظام المعقد للموارد المياه باستخدام البرمجة الديناميكية DP والبرمجة الديناميكية التفاضلية المنفصلة DDDP. بالاضافة الى حل نموذج الامثلية البرمجة الديناميكية النموذجي، تم اعتماد نموذج المحاكاة لتحقيق عملية تقريبية للتشغيل الأمثل قدر الإمكان، والحفاظ على مستوى التخزين والإطلاقات داخل المحددات. من أجل الوصول إلى الحل الأمثل لمشكلة الخزان عمليا، تم استخدام طريقة رقمية للبرمجة الديناميكية لتحديد القرار المتسلسل الامثل، مع الأخذ بعين الاعتبار القيود الفعالة المرتبطة بالمشكلة. البرمجة الديناميكية التفاضلية المنفصلة هو إجراء لحل العديد من المشاكل التي تمت صياغتها بالفعل كمخططات ديناميكية وبالتالي تقليل متطلبات الذاكرة وحفظ الوقت الحسابي. تم تطبيق نموذج الامثلية على عمليتين افتراضيتين تمثلان الحالات القصوى، وهما سنتين متتالية نسبيًا من الرطوبة وسنتين جافتين متتاليتين نسبياً. شكلت بيانات التدفق التاريخي لـ (240) شهرا (من أكتوبر 1988 إلى سبتمبر 2005) كبيانات الإدخال إلى نموذج الامثلية للحصول على منحنيات القاعدة (العلوي، المتوسط ​​، المنخفض). وتم تجنب حالة الفيضان داخل خزان العظيم بشكل كامل وقد أظهرت نظام التشغيل الامثل عجزًا في تلبية متطلبات سد العظيم. وقد بينت النتائج بان التشغيل الامثل للسنتين الرطبتين القصوى مسيطر عليها من ناحية الفيضان ونسبة عجز 9.3–59.1 م3/ثا من أصل 34.2% من الاحتياج الكلي وللسنوات الجافه القصوى 11.8 – 81.2 م3/ثا من أصل% 57.3 من الاحتياج الكلي.This research is set out to review of “optimum the water complex resources system by using dynamic programming DP and Discrete Differential Dynamic Programming DDDP, Beside a solution of formulated DP optimization model, the model of simulation was adopt for achieve the operation as close to optimum operation as possible, with the keep level of storage and releases within their targets”. In aiming at the optimal solution of the reservoir – operation problem, (DP) represents a numerical method which is used to determine the optimal sequential decisions, taking into consideration an effective constraints associated with problem. DDDP is the solution procedure of many problems which already formulated as dynamic – programming ones. It is reduce the memory requirements and save computational time. The Optimization model was applied for “two operations hypothetical represented by the cases of extreme, namely consecutive to the relatively of two wet years and two consecutive the relatively of dry years”. The data to the historical inflow for “(240) months are (from Oct. 1988 to Sep. 2005) was form to the data input to a model of optimization for found rule curves (lower, average and upper)”. A flooding state within Al_Edhaim Resevoir has been fully avoided. “The policy to the optimization of operation is shown a deficiency in satisfying downstream Al-Edhaim Dam demands”. “The optimization of the operation for two consecutive wet years would be full capable controlling expected floods, so as to the deficiency would be from 9.3–59.1 cumecs total of 34.2% of demand, then the optimization of the operation for two consecutive dry years would be from 11.8 – 81.2 cumecs total of 57.3 % of the whole demand"