- Mogahid Abed El Rahman Yousif - مجاهد عبد الرحمن يوسف عبدالرحمن
- published on 3/1/2014
- Use of glass fibre reinforced epoxy in artificial teeth
Textile materials have found important non-traditional uses during the last decade.
Medical textiles are one of the new emerging uses of technical textiles especially in
denture. Glass, carbon, boron, and aramid fibres are being used to reinforce different
types of matrix materials to gain some special properties for specific end use. In this
work, multilayered glass fibre preform was used to reinforce epoxy resin and the
produced composite was tested for some physical and mechanical properties. The results
were then compared to those of the traditionally used materials in dentistry. The work
had shown that the glass fibre reinforced epoxy polymer can be used in making artificial
teeth in rather better properties compared to the now-a day used materials.
KEYWORDS: glass fibre, multi-layer composites, epoxy resin, hand-lay-up method,
curing, artificial teeth, tensile and shear properties.
- Azhari Siddeeg Abdelwahab Ahmed - ازهري صديق عبد الوهاب احمد
- published on 1/16/2018
- Quality characteristics of yoghurt made fromvarious blends of camel’s andcow's milk
Milk and its products are of high nutritional value and are of great importance in human nutrition. In Sultanate of Oman, cow’s milk is normally used in the production of various dairy products. However, in Salalah and the surrounding area camel milk is more used than cow’s milk. The aim of this study is to enhance the utilization of camel milk for the production of yoghurt from blends of camel and cow’s milk. Three types of yoghurts were made from 100% cow’s milk and blends of camel and cow’s milk in the proportion of, 15: 85% and 30: 70% of camel's and cow's milk, respectively. Milk as well as their products were subjected to chemical, microbiological and sensory evaluation analyses using standard methods. The results obtained showed very slight difference between the chemical composition of camel's and cow's milk. The contents of the chemical components of the last two blends of camels and cow’s milk were almost identical. On the other hand, the microbial analysis showed that the camel and cow’s milk were free from Coliformbacteria. However, it was found that very small numbers of Coliform bacteria were found in the milk blends at the levels of 0.8 x10 and 0.9×10for the samples of 30: 70% and 15: 85%. Camels and cow’s milk blends, respectively. The total bacteria count in the cows and camels milk were 0.3 ×10² and 0.1×10² respectively, while it was 0.5 ×10² and 0.8 ×10² in the camel's and cow's milk blends of 15: 85 % and 30: 70% respectively. The results also indicated the presence of very small numbers of yeasts and molds in all the milk samples. It was found to be 0.3 × 10, 0.2 × 10 , 0.4 × 10 and 0.1×10² in the camel's and cow`s blends of 30: 70% and 15:85% respectively. The acidity of the various types of yoghurts i.e. type A ( blends of 30:70 %); type B (15: 85%) and type C (0:100%) camels to cow’s milk was the same in the fresh product 1.05% However, it progressively increased with the increase of storage period at a 6° C , where it reached after 10 days of storage 1.1 % in type A yoghurt; 1.07% % in type B yoghurt and 1.11 % in type C yoghurt with a concomitant decrease in the pH values. There was also a progressive decrease in the protein and total solids contents and a progressive increase in the fat contents of all the types of yoghurts with the increase in the storage period for all the types of yoghurts. The sensory evaluation results indicated that the 100% cow’s milk yoghurt (type C yoghurt) scored the highest overall acceptability and that type B yoghurt (15: 85% camels / cow’s milk scored the second best overall acceptability. It is recommended that camel`s milk utilization enhancement to be explored by its incorporation in yoghurt manufacture.
published in European Academic Research
- - خالد يعقوب احمد يعقوب
- published on 5/1/2017
- Dose Survey in Adult Patients during Simulation for Radiotherapy Planning
The DoseCal software has been used to assess the entrance skin doses (ESD) , effective doses (ED) and organ doses (OD) of cancer patients undergoing radiotherapy planning of pelvis (AP) , head (RLAT & LLAT), lumber spine (AP) and rectum (PA) in national cancer institute (NCI) , equipped with simulator x-ray machine with tube filtration 2mm Al. The mean ESD , ED and OD of four different projections were calculated using the software. the mean ESD calculated were 1.39mGy, 0.334mGy, 0.433mGy, 0.479mGy, 0.486mGy , the mean effective doses were 0.283 mSv, 0.003 mSv, 0.004 mSv, 0.045 mSv, 0.004mSv for pelvis (AP) , head (RLAT & LLAT) , lumber spine (AP) and rectum (PA) respectively . The mean ESD to the sensitive organs around the pelvis, head, lumber spine, and rectum were 0.172mGy, 0.217mGy, 0.925mGy, and 0.549mGy for lens of the eye, ovaries, testicles and urinary bladder respectively.
Keywords: radiotherapy, simulator, entrance skin dose (ESD), effective doses (ED), organ doses (OD).
- Mogahid Abed El Rahman Yousif - مجاهد عبد الرحمن يوسف عبدالرحمن
- published on 11/1/2011
- Dental interventions are safe during pregnancy
Objectives: To investigate the safety of tooth extraction and other dental interventions during pregnancy.
Methods: Pregnant ladies with dental problems were seen by an obstetrician and a dentist. Simple cases were treated medically. Severe cases were identified. When surgical intervention was indicated due to abscess formation or disturbance of sleep, patient consent was taken and the necessary treatment was performed. A contact number was given to each patient and their addresses were taken. All treated patient were asked to report seven days latter for follow up of the dental condition and the pregnancy wellbeing.
Results: This study involved 97 pregnant ladies, in different gestational ages, 50.5% of them were in the first trimester. Patients from urban area were 65.9%. The population of this study included patients with pregnancy order up to 8 however 23.7% of them were primigravidae. Some of these ladies (30.0%) gave past history of previous pregnancy complications. Each patient presented with more than two symptoms of the following: pain, disturbance of sleep, difficulty in food chewing, bleeding from the gum and earache. All patients had clinical evidence of infection either pulpitis, gingivitis or both. The main underlining problem of these participants was tooth caries. The surgical dental interventions included; tooth extraction, scaling, filing and root canal treatment.
Conclusion The dental intervention during pregnancy using local anaesthesia is safe. The severe pain, difficulty of feeding and disturbance to sleep due oral/dental diseases may cause more danger to mother and her fetus than dental intervention.
published in Gezira journal of Health Sciences
- - السيد السر النقرابي مصطفي
- published on 1/1/2011
- Analysis of government policies impact on cotton and wheat production in Gezira Scheme (seasons 2003-2007)
Government policies impact on cotton and wheat production in Gezira Scheme The policy analysis matrix (PAM) had been used to measure nominal protection coefficient of outputs (NPCO), nominal protection coefficient of inputs (NPCI), effective protection coefficient (EPC), domestic resources coefficient (DRC), international value added (IVA) and profitability coefficient (PC). The (PAM) parameters would be used to assess the international competitiveness, protection measures and comparative advantages of the Gezira scheme products, mainly cotton and wheat. The Policy Analysis Matrix (PAM) The policy analysis matrix method has been used as one of the modern tools to analyze the agricultural policies to derive some indicators and standards of measuring the impact of the government agricultural policies on the agricultural sector (Table 1). It has been initiated to analyze market distortions and policy interventions in terms of their effects on the vertical commodity system from its initial production in the farm through the primary procurement, processing and marketing stages (Pearson and Monke, 1989). Table 1. the Policy Analysis Matrix (PAM) structure. Revenues Costs Profit Tradable inputs Domestic factors Private prices A B C D Social prices E F G H Divergences I J K L Source: Person and Pearson (1989). Where: A = total revenue in private price (market prevailing price). B = cost of tradable inputs in private price. C = cost of domestic factors in private price. D = private profit. E = total revenues in social price (efficiency price). F = cost of tradable inputs in social prices. G = cost of domestic factors in social prices. H = social profits. The matrix is thus made up by the following identities: Private or financial profit (D) D=A-B-C Social profit (H) H=E-F-G International value added (IVA) E-F=H+G Output transfers (I) I=A-E E.E.M.H, Elnagarabi, M.S.M. Alhag, & A. E.M. Alamin Input transfers (J) J=B-F Factors transfers (K) K=C-G Net transfers (L) L=D-H=I-J-K The shadow exchange rate (SER) is the economic price of foreign currency. There is a common misconception that if the market for foreign exchange is a free float, the shadow exchange rate (SER) is equal to the market exchange rate. That would be the case only if there were no taxes and subsidies on the demand and supply of tradable goods, if all commodities and factors were priced at their economic value, and if the current account deficit was sustainable. In all cases, the (SER) will diverge from the market or official exchange rate (OER). This method of shadow pricing is tedious and time consuming and consequently rarely followed. Instead, non-traded goods are generally valued at economic prices by the use of conversion factors. A conversion factor is a short-cut method for converting prices of non traded goods and services into border prices. At the most aggregated level a single conversion factor, the standard conversion factor (SCF) is used for this purpose. The (SCF) is derived by taking the ratio of all exports and imports at border prices to their value at domestic prices. Shadow prices of non-traded items are then obtained by multiplying the (SCF) with the market prices. This reduces the market prices to their real economic value. The formula for the (SCF) is: SCF = _M + X_________ ……………… (1) (M + D) + (X - T) Where: M = value of imports at border prices X = value of exports at border prices D = total import duties T = total export taxes Based on the collected data, the estimated conversion factor used was 0.94 (Alhag, 2009). Nominal Protection Coefficient of Outputs (NPCO) It measures protection and can be calculated by the following formula: NPCO = A/E……………………………………………………… (2) Protection Coefficient of Nominal Inputs (NPCI) It measures the actual divergences or distortions between the domestic prices of tradable inputs and its boarder or world price. It was obtained by dividing the tradable inputs value in private prices (B) by its value in social prices (F) NPCI = B/F…………………………………………………………… (3) Government policies impact on cotton and wheat production in Gezira Scheme Effective Protection Coefficient (EPC) It is a comparison between the value-added measured in private prices (A-B) by the value added measured in social prices (E-F), and it is a more efficient measure of the policy effect, so it is assessing the pure impact of the policies on each of the inputs and outputs and it could be measured as EPC =A-B/E-F………………………………………………….. (4) Domestic Resources Coefficient (DRC) Also called social cost-benefit ratio and it is used to measure the domestic production efficiency relatively to the world markets. In other words, it measures the economic efficiency or the comparative advantages in the international exchange average and it clarifies the fact that if the social costs and profits to produce a commodity is better than export it. Also, it compares the social cost of using the domestic factors (G) to the production value added in social prices (E-F), i.e. it measures social domestic resources cost ratio and the comprehensive efficiency of the commodity system as follows DRC = G/E-F……………………………………………………. (5) International Value Added (IVA) The IVA is defined as the revenue of the crop minus the imported (tradable) inputs expressed in foreign currency. It is equal to (A-B) in financial analysis and (E-F) in economic analysis. It is an absolute measure of competitiveness. A crop with a positive IVA indicates positive foreign exchange earnings or saving. The principal defect of such a measure is that it neglects the effect of domestic factors. IVA= E-F……………………………………………………………… (6) Profitability Coefficient (PC) Profitability coefficient is a measure of absolute competitiveness and the incentives of commodity. It is calculated as a ratio of private profitability to social one. PC = PP/EP =D/H……………………………………………………. (7) PP = private profitability EP = economic profitability E.E.M.H, Elnagarabi, M.S.M. Alhag, & A. E.M. Alamin RESULTS AND DISCUSSION The policy analysis was employed to calculate the following: 1. The nominal protection coefficient of outputs: The value of nominal protection coefficient of output (NPCO) for cotton in all seasons was less than one that means that cotton output has been taxed, and the government is not protecting the cotton production (Table 2). Nominal protection coefficient of outputs (NPCO) for wheat was greater than one, indicating that wheat output has been subsidized (10 SDG per sack) and the government was protecting wheat production. Adam (1996) revealed that cotton was heavily taxed, however, discrimination against cotton appeared to be substantial during the three years of the program. In the seasons from (2003 to 2007), the discrimination against cotton was still existing despite the slight improvement from an average of 0.28 in the beginning of the liberalization program to 0.77 in the seasons of this study (Table 2). As known earlier, the government reduced export taxes to 5% for all agricultural exports except cotton and gum Arabic, for whish export tax was reduced to 10%. According to Albashir (2005), the percentage of taxes and fees on cotton were: The federal government: 16.5% Gezira state and social services: 7.8% (Zakat after subtracting the production cost: 5%) On the other hand, positive results were achieved in wheat protection that appears in the increase of NPCO from less than one at an average of 0.30 in seasons from 1991 to 1993 to an average of 1.09 in the years of the study (Table 3). Table 2. Nominal protection coefficient of outputs (NPCO) for cotton and wheat in the Gezira Scheme, seasons (2003/04 – 2006/07). Season Cotton Wheat 2003/04 0.75 1.09 2004/05 0.73 1.08 2005/06 0.79 1.08 2006/07 0.8 1.1 Source: Alhag (2009). Government policies impact on cotton and wheat production in Gezira Scheme Table 3. Nominal protection coefficient of outputs (NPCO) for cotton and wheat in the Gezira Scheme, seasons (1991/92 – 1992/93) Season Cotton Wheat 91/92 0.24 0.45 92/93 0.31 0.14 Source: Adam (1996) 2. The nominal protection coefficient of inputs The value of nominal protection coefficient of input (NPCI) for cotton and wheat in all seasons under consideration were greater than one which means the both crops inputs had been taxed (Tables 4 and 5). Table 4. Nominal protection coefficient of inputs (NPCI) for cotton and wheat in the Gezira Scheme, seasons (2003/04 – 2006/07). Season Cotton Wheat 2003/2004 1.06 1.06 2004/2005 1.06 1.06 2005/2006 1.06 1.06 2006/2007 1.06 1.06 Source: Alhag (2009). Table 5. Nominal protection coefficient of inputs (NPCI) for cotton and wheat in the Gezira Scheme, seasons (1991-93). Season Cotton Wheat 91/92 0.77 0.38 92/93 0.50 0.62 Source (Adam, 1996) In the beginning of the liberalization program, results implied support to farmers through inputs subsides by the government as shown in Table 5 for both products, whereas in the seasons under consideration, cotton and wheat suffered from high taxation. 3. The Effective Protection Coefficient: For cotton, in all seasons (2003 – 2007), EPC was less than one (Table 6). This means that the adopted policy was discriminating against the cotton producers and indicated that the production of cotton had not protected through the policy intervention. For wheat, the value of EPC was greater than one (subsidized) as shown in Table 6. This means that the adopted policy provided positive incentives for producing wheat. E.E.M.H, Elnagarabi, M.S.M. Alhag, & A. E.M. Alamin Table 6. Effective protection coefficient of inputs (EPC) for cotton and wheat in the Gezira Scheme, seasons (2003/04 – 2006/07). Season Cotton Wheat 2003/04 0.58 1.09 2004/05 0.58 1.08 2005/06 0.66 1.08 2006/07 0.53 1.11 Source: Alhag (2009). 4. The Domestic Resources Coefficient (DRC) The results obtained shows that the values of (DRC) of all seasons under the study for both products are less than one (Tables 7 and 8). This result indicates that the Gezira scheme has a comparative advantage in producing both cotton and wheat and the use of the domestic factors is socially profitable. When comparing these results to those reported by Adam (1996), it is clear that the comparative advantage of cotton is deteriorating (Tables 7 and 8). Table 7. Domestic Resources Coefficient (DRC) for cotton and wheat in the Gezira scheme (2003/04 – 2006/07) Season Cotton Wheat 2003/2004 0.37 0.33 2004/2005 0.33 0.30 2005/2006 0.30 0.37 2006/2007 0.54 0.24 Source: Alhag (2009). Table 8. Domestic Resources Coefficient (DRC) for cotton and wheat in the Gezira scheme (1991/92 – 1992/93) Season Cotton Wheat 91/92 0.19 0.36 92/93 0.26 0.16 Source: Adam (1996) The comparison indicated that both crops were profitable and competitive, but the difference between the lowest ratio (0.19) in the first season (1991/1992) and the last season (2006/2007) (0.54) indicated a trend of increase in the value of the DRC throughout the years. This was a bad sign showed that the situation tended to get worse in the comparative advantage of cotton. Government policies impact on cotton and wheat production in Gezira Scheme 5. International Value Added (IVA): It is defined as the revenue of the traded crop minus the imported tradable inputs expressed in foreign currency. S crop with a positive IVA indicated that it is a net earner of foreign exchange. It measures the international competitiveness of the product and is an absolute measure of competitiveness. These results showed that the production of these products in the Gezira Scheme was competitive and it provided positive foreign exchange earnings, particularly for wheat in the season 2006/2007 as compared to the previous seasons. The results showed positive values of IVA for both crops in both periods. These results meant that cotton and wheat production in the Gezira scheme were competitive and provided positive earnings from cotton export and local sale of wheat. However, it appeared that the adopted policies had been in favor of wheat (food crop) which clearly appeared in the season 2006/07 as shown in Tables 9 and 10. Table 9. International value added (IVA) for cotton and wheat in the Gezira scheme (seasons 2003/2004 – 2006/2007). Season Cotton (SD) Wheat (SD) 2003/04 263 205 2004/05 322 257.1 2005/06 343 236.4 2006/07 215.4 423 Source: Alhag (2009). Table 10. International value added (IVA) for cotton and wheat in the Gezira scheme (seasons 1991/1992 – 1992/1993). Season Cotton (SD) Wheat (SD) 91/92 296.4 133.27 92/93 291.5 163.96 Source: Adam (1996). 6. The Profitability Coefficient (PC) Results obtained for PC indicated that all ratios of cotton is less than one which confirmed that the government discouraged farmers to produce cotton and indicated that they would only receive approximately half of the profit that they would receive in the absence of government policy and that was clearly noticed in season 2006/07 (Table 11). The ratio for wheat were greater than one in all seasons so that the government provided incentives and favored the production of wheat and the farmer was receiving 0.2% as a result of government policy (Table 11). E.E.M.H, Elnagarabi, M.S.M. Alhag, & A. E.M. Alamin Table 11. Profitability Coefficient (PC) for cotton and wheat in the Gezira scheme (2003/04 – 2006/07) Season Cotton Wheat 2003/2004 0.37 1.19 2004/2005 0.39 1.15 2005/2006 0.59 1.19 2006/2007 0.01 1.2 Source: Alhag (2009). Conclusions and policy implications The study was carried out to analyze the impact of the agricultural specific policies adopted by the |Sudanese government on the protection, comparative advantage and competitiveness on cotton and wheat production in the Gezira Scheme for the period 2003-2007. Results obtained indicated that these policies imposed implicit taxes on cotton and wheat inputs over the years of the study, provided incentives for wheat production, discouraged cotton production and there were still comparative advantages in cotton and wheat production in the Gezira Scheme. The policy implications of the protection, comparative advantages and competitiveness indicators are that these policies have failed to improve the overall performance of the Gezira Scheme. REFERENCES Adam, M. A. 1996. The policy Impacts on farmer's Production and Resource Use in the irrigated Scheme of Gezira, Sudan. Ph. D Thesis, University of Berlin, Germany. Al Bashir, A.A. 2005. Economics of cotton in the Gezira Scheme (season 200-2005). M.Sc. Thesis, University of Gezira, Sudan. Alhag, M.S.M. 2009. Analysis of Government Policies on Cotton and Wheat Production in Gezira Scheme. M.Sc. Thesis, University of Gezira, Sudan. Eldaw, A. M. 2004. Gezira scheme: Perspectives for Sustainable Development. German Development Institute, Bonn, retrieved from: www.die-gdi.de Elnagarabi, S. E. 1996. The impact of Privatization on the Gezira scheme. M.Sc. Thesis, University of Gezira, Wad Madani, Sudan. Person, R. and Monke. 1989. The Policy Analysis Matrix for Agricultural Development retrieved from:www.stanford.edu World Bank. 1986. World Development Report Washington DC.
published in Gezira J. of agric. Sci. 8 (1): 25-36 (2010)