Digital Repository for University of Tripoli

Background: The concept of pharmacovigilance is not well known in Libya and its practice is still in the early stages. Aims: This study aimed to determine the knowledge, attitudes and practices of pharmacists in Tripoli, Libya about pharmacovigilance and the reporting of adverse drug reactions. Methods: A cross-sectional study was conducted from October 2019 to February 2020 of working pharmacists randomly selected from pharmacies in Tripoli. Participants were eligible for inclusion if they had a degree or diploma in pharmacy from a recognized university or institute. Data were collected using a validated self-administered questionnaire. Results: Of 500 pharmacists selected, 408 completed the questionnaire. The pharmacists' knowledge of pharmacovigilance and reporting of adverse drug reactions was poor overall: only 28.9% correctly defined pharmacovigilance and 14.7% knew about the existence of a centre for pharmacovigilance in Libya. The attitudes of the pharmacists to pharmacovigilance was positive: 77.2% believed that pharmacovigilance needed to be included in the pharmacy curriculum and 73.0% said that they would practice pharmacovigilance if trained. Pharmacists depended mostly on drug information leaflets to update their knowledge on adverse drug reactions. Conclusion: Given the pharmacists' low level of knowledge about pharmacovigilance but their readiness to become involved if trained, training programmes should be introduced for practising pharmacists to improve their knowledge and encourage their active participation in pharmacovigilance. Regulators need to reinforce the importance of reporting adverse drug reactions and implement pharmacovigilance policies in the Libyan health care system.
Ahmed Elbadri M Atia(7-2021)

Evapotranspiration is an important component in many hydrological, ecological and agricultural studies. There are many available direct and indirect methods to determine the evapotranspiration rate. In this study, alternative model based on multilayer Artificial Neural Network (ANN) using the backpropagation algorithm was proposed to estimate evapotranspiration as referred to pan evaporation. The meteorological data used in this study were obtained from Al-Zahra and Al-Zawia stations which located on the coastal area of western Libya lie. The input data were consisted of mean temperature, mean relative humidity and mean of actual sunshine hours of consecutive years (1995, 1996, 1997 and 1999). The performance of the ANN model was evaluated against a set of data that never seen by the model during the training phase. The evaluation of ANN model was also performed against Blaney and Criddle, Radiation and modified Penman methods. The results showed that ANN forecasts were superior to the ones obtained by Blaney and Criddle and Radiation methods. Due to its little input data, ANN is considered to be more efficient as compared with the modified Penman method. However, this application of ANN as a fitting tool should be useful in evapotranspiration modeling. Keywords: Evapotranspiration Pan evaporation, Artificial neural networks, Backpropagation algorithm.
Ahmed Ibrahim Ekhmaj(1-2012)

Many attempts have been created to determine wetting pattern under trickle irrigation using sophisticated mathematical and numerical models, required detailed information concerning soil physical properties and too complicated for routine use. For this reason, an alternative methodology is proposed, which combines artificial neural networks (ANNs), laboratory and field experiments. The model input parameters were saturated hydraulic conductivity, application rate, volume of water applied and average change of moisture content. The model outputs were surface wetted radius and vertical advance of wetting front. A total of 280 and 100 vectors were used to train the ANNs model for surface wetted radius and vertical advance of wetting front estimations, respectively. To test the ANNs model, a total of 132 and 76 vectors were selected in case of surface wetted radius and vertical advance of wetting front estimations, respectively. Results of the test show that the surface wetted radius and vertical advance of wetting front can be predicted with a determination coefficient (r2 ) of 0.80 and 0.81 for the surface wetted radius and vertical advance of wetting front, respectively. Additionally, the ANNs approach was found to produce equally or more accurate descriptions of wetting pattern as compared to several analytical and empirical models which suggested for point source trickle irrigation design.
Ahmed Ibrahim Ekhmaj, A.M. ABDULAZI, A.M.ALMDNY(1-2007)

The infiltration rate is an important parameter in soil, hydrological, ecological and agricultural studies. It plays the main role as the input parameter in models for water flow and solute transport in the vadose zone. In this study, Multilayer Artificial Neural Network "ANN" using the backpropagation algorithm was selected to estimate the steady infiltration rate covering different types of Libyan soils. The activation function was selected LOGSIG in the middle and exit layers. The input data were the percentage of sand, silt and clay, bulk density, saturated hydraulic conductivity and the volumetric water content in soil at -10 kPa. The performance of the ANN models was evaluated against a set of data that never seen by the model during the training phase. Multivariate linear regression model (MLR) based on the percentage of silt, saturated hydraulic conductivity and volumetric water content in soil at -10 kPa was also developed to determine infiltration rate for evaluation purpose. The results obtained in this study showed a good agreement between the measured data and the ANN simulated. The values of mean absolute error and root mean square error were slightly smaller in ANN steady infiltration rate model compared to the developed Multivariable linear regression model to estimate the infiltration rate. Although the results of these comparisons encourage the using ANN in practice, it would be valuable to have large local soil database from many different sites, in order to make a stronger assessment of the ANN models.
Ahmed Ibrahim Ekhmaj(10-2010)

Multilayer Artificial Neural Networks (ANNs) with the backpropagation algorithm were used to estimate the decrease in relative saturated conductivity due to an increase in sodicity and salinity. Data from the literature on the relative saturated hydraulic conductivity measured using water having levels of sodicity and salinity in different types of semiarid soils were used. The clay content of these soils is predominantly montmorillonite. The input data consisted of clay percentage, cation exchange capacity, electrolyte concentration, and estimated soil exchangeable sodium percentage at equilibrium stage with the solution applied. The data was divided into three groups randomly to meet the three phases required for developing the ANNs model (i. e. training, evaluation, and testing).The activation function selected was the TANSIG layer in the middle, while the exit function was the PURELIN layer. The comparisons between the experimental and predicted data on relative saturated hydraulic conductivity during training and testing phases showed good agreement. This was evident from the statistical indicators used for the evaluation process. For the training phase, the values of mean absolute error (MAE), root mean square error (RMSE), the correlation coefficient (r) and the determination coefficient (R2) were 0.08, 0.13, 0.91, and 0.83, respectively. The performance of the ANNs model was evaluated against a part of the data selected randomly form the whole set of data collected (i. e. data not used during the model testing phase). The resultant values for MAE and RMSE, r and R2 were 0.12, 0.16, 0.82 and 0.68, respectively. It should be noted that many factors were not considered, such as soil pH, type of clay, and organic matter, due to the limitations of the data available. Using these factors as input in ANNs might improve model predictions. However, the results suggested that the ANNs model performs well in soils with very low levels of organic matter.
Younes Daw Ezlit, Ahmed Ibrahim Ekhmaj, Mukhtar Mahmud Elaalem(5-2014)

المخاطر التي تواجه المشروعات المقامة بنظام B.O.T
خلود خالد بيوض (3-2021)

النــزوح القسري وأسبابـــه في القانــون الدولي الــعام
عبد الحكيم ضو طاهر زامونه(3-2021)

Summary: One of the main characteristics of trickle irrigation system is that water leaving an emitter enters the soil and moves both laterally and vertically. There has been much speculation on the shape and moisture distribution within the wetted soil volume. This knowledge is important in the design, operation and management of a trickle irrigation system. A simulation study of soil water distribution under a prairie field in Tripoli Libya, by the use of the two dimensional model Hydrus 2D model was carried out. Sandy soil was irrigated using surface point source with application rates of 1.5, 2, 2.7, 3, 3.5, 4.5, 4.8 and 6 l/h. The surface wetted radius, vertical advance of wetting front and the distribution of moisture content in the soil profile were determined. Three statistical criteria were used to compare the quality of simulation results, such as mean bias error (MBE), root mean square error (RMSE) and Theil’s Inequality coefficient (U). Simulation positions of the wetting front were in agreement relative to the observed measurements of the wetting front. Specifically, in the lateral, the experimentally determined wetting front was closely estimated by the model. In the downward direction the simulated wetting front advanced much slower than the observed especially at later stage of infiltration. Considering the difficulties in estimating the dynamic water conditions in the field there was generally good agreement (especially in the lateral direction) between the measured and simulated values. In the deeper downward direction the simulated moisture content distributions were less than the measured. On the other hand, the Hydrus_2D model described the water content distribution quite well at relatively high levels of moisture contents; however, it did not do as well at lower moisture content. The discrepancies between the simulated and measured values may be due to variation in the size of the surface source of water during infiltration and to the natural variation of soil properties. However, due to the complex mechanisms of water movement under the complicated boundary and initial conditions from a surface point source the results support the use of Hydrus 2D as a tool for investigating and designing point source trickle irrigation system. Keywords: Trickle irrigation, wetting front, soil moisture distribution, Hydrus _2D model
Ahmed Ibrahim Ekhmaj, M.S.M. Amin, Abdul Hakim Almdny, W. Aimrun, .M. Abdulaziz, (1-2006)