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Background: The medical profession is one of the most highly respected and desired professions among students worldwide, most likely because it provides opportunities for both a financially and socially rewarding career. However, while it has been quite established that factors such as self-interest, family pressure, friend pressure, and socioeconomic status do influence the choice of medicine among students worldwide, the exact reasons for an individual to enter a medical school may actually vary worldwide. An institutional based descriptive cross-sectional study was conducted at University of Khartoum in the year 2022 with a random sample of 330 students that was obtained from the medical students at the The University of Khartoum, Faculty of Medicine using stratified random sampling to comprehensively explore factors influencing medical students to opt in/out medical careers. Results: Self-interest was the most common factor influencing opting in (choosing) medical profession (70.6%) (n= 233), followed by getting a very high score in high-school that qualifies into the faculty (55.5%) (n= 183). Better job opportunities in the future was the third factor for (45.5%) (n= 150) for our subjects. Regarding the factors affecting medical students’ choices, parental pressure was the main factor (37.0%) (n= 122), followed by other relatives' pressure (12.4%) (n= 41), and 4.2% (n= 14) chose Peer pressure. 59.7% (n= 197) of the participants stated that they were not affected by any of these factors. Regarding the general perception of the medical profession by society, most of our participants (65.8%) (n= 217) chose “With good career opportunities”, 62.4% (n= 206) chose “Prestigious”, 55.8% (n= 184) chose “Well-paid”, while 5.8% (n= 19) believed that it is “Not appreciated at all”, and statistically significant association was found between the type of admission & parent pressure (p value 0.01). out of 330 participants, (56.1%) (n=185) have opted out i.e.lost their interest or regretted their choice of medical career. Regarding the factors causing opting out, academic difficulties was the most common factor (37%) (n=122) followed by Multiple suspensions of education (35.2%) (n=116), Current political & security conflicts in Sudan (29.7%) (n=98), Poor quality of education (24.8%) (n=82), health-related conditions (7.3%) (n=24), Financial difficulties (6.4%) (n=21). Also (3.3%) (n=11) mentioned other options. The proportion of students having regrets for the medical profession was significantly higher among females. Over one third of the participants reported having depressive symptoms more than half days of the week . Conclusions: This study has surprisingly found that the majority of current medical students at the University of Khartoum have already lost their interest or regretted their medical career choice. Academic difficulties, multiple suspension of education, and poor quality of education were the most common reasons that caused medical students to opt out of the medical career. Self-interest and getting high scores in high school were the most common reasons for opting in a medical career, and parents' pressure was the most common factor to influence the choice. Also surprisingly, more than one third of students were found to have symptoms of depression, a statistically significant correlation was found between opting out and having “little interest or pleasure in doing things” (anhedonia) over the last two weeks and also between opting out and feeling “down, depressed or hopeless” over the last two weeks, these two findings highly suggest that symptoms of depression can very well be one of the hidden factors that influence career choice regret, yet it is fair to say you can never tell which one comes first.

This study investigated the role of the dietary lipid Conjugated Linoleic Acid (CLA) as a 50:50 mixture of 9:11 CLA and 10:12 CLA and these two isoforms used individually, in regulating the carboxymethyllysine (CML) induced inflammatory response in human monocytic, macrophage and endothelial cells. CML is a glycated amadori product that has a crucial role in activating the inflammation in type 2 diabetes (T2D). All three forms of the lipid at non-toxic levels were capable of significantly reducing the release of two inflammatory cytokines (TNF-α and IL-6) in monocytes and macrophages and IL-6 in endothelial cells. In contrast the non-conjugated Linoleic Acid (LA) did not significantly reduce these cytokines in any of the cell types investigated. All isomerswere capable of activating both forms of the nuclear transcription factors Peroxisome Proliferator Activated Receptors (PPAR) α and in monocytes and macrophages. CLA induced significantly the activation in the transcription factor important in regulating the inflammatory response, nuclear factor-kappa B (NF-B). However, in cells treated with CML, CLA significantly reduced the activation of NF-B as measured by DNA binding in cells pre-treated with CML-suggesting an ability to trensrepress the activity of NF-B, possibly in conjunction with the PPARs and supporting an anti-inflammatory role for the lipid in activated cells. All three forms of the lipid were significantly able to regulate expression of the receptor for glycated proteins (RAGE) in monocytes, macrophages and endothelial cells. Gene reporter assays demonstrated that in endothelial cells, that CLA was capable of suppressing the transcriptional activity of promoters which contain promoters for NF-κB response elements, either as part of a recombinant construct or as a cloned fragment of the human RAGE promoter. Hence, in conclusion it would appear that the CLAs investigated in this study could significantly suppress the inflammation in diseases such as T2D through their ability to suppress NF-B leading to down-regulation of RAGE expression. Furthermore, these events appear to be consistent for all three forms of CLA investigated and in all three cell types-all with a critical role in the development of atherosclerosis.

BACKGROUND: The standard triple therapy has lost a considerable proportion in it efficiency in treating Helicobacter pylori infection. As such several alternatives and adjuvants have been proposed. One the most promising modulation is the supplementation this therapy with probiotics. AIMS: This study aimed to investigate the efficiency of probiotic supplementation to traditional triple therapy in the eradication of Helicobacter pylori infection and alleviation of side effects. PATIENTS AND METHODS: This is a cross-sectional study included 310 consecutive patients newly diagnosed with gastritis or dyspepsia and infected with H. pylori. Patients were randomly divided into three groups based on treatment regimes. Group A: 100 patients received triple therapy consisting of omeprazole, amoxicillin and levofloxacin for two weeks. Group B: 100 patients received tinidazole, levofloxacin and omerprazole for two weeks. Group C: 110 patients received the second protocol plus the probiotic. All patients were reinvestigated four weeks after accomplished treatment by stool antigen test for H. pylori. RESULTS: The rate of successful H. pylori eradication was 77.74%. In multivariate analysis, each of age≤ 35 years (OR=0.51, 95%CI=0.28-0.93), being married (OR= 0.37, 95%CI=0.21-0.71), never smoker (OR= 0.55, 95%CI=0.32-0.95) and treatment regime with triple therapy supplemented probiotics (OR= 3.36, 95%CI=2.5-21.7) were significantly associated with increased the eradication rate. The overall incidence of side effect in group C was (7.27%) was lower than that B (19%) with significant difference, and group A (15%) with no significant difference. CONCLUSIONS: The use of probiotics as an additive for the standard triple therapy significantly increases the eradication of H. pylori and may reduce the incidence of side effect of the traditional therapy.

This paper describes the methods used by Team Cassandra, a joint effort between IBM Research Australia and the University of Melbourne, in the GEFCom2017 load forecasting competition. An important first phase in the forecasting effort involved a deep exploration of the underlying dataset. Several data visualisation techniques were applied to help us better understand the nature and size of gaps, outliers, the relationships between different entities in the dataset, and the relevance of custom date ranges. Improved, cleaned data were then used to train multiple probabilistic forecasting models. These included a number of standard and well-known approaches, as well as a neural-network based quantile forecast model that was developed specifically for this dataset. Finally, model selection and forecast combination were used to choose a custom forecasting model for every entity in the dataset.

A multi-resolution approach to dynamic programming is presented, which reduces the computational effort of solving multistage optimization problems with long horizons and short decision intervals. The approach divides an optimization horizon into a series of subhorizons, discretized at different state space and temporal resolutions, enabling a reduced computational complexity compared to a single-resolution approach. The method is applied to optimizing the operation of a residential energy storage system, using real 1-min demand and rooftop PV generation data. The multi-resolution approach reduces the required computation time, allowing optimization to be rerun more frequently, increasing the robustness of the receding-horizon-control approach to forecast errors. In an empirical study, this increases the cost-saving offered by a 2 kWh behind-the-meter battery energy storage system by 120% on average, compared to an approach using a single fine-grained resolution.

The study aims to clarify the role of banking finance on developing housing sector in Sudan (2011- 2018). Descriptive analytical and case study approaches were used. The study reached several results, including a weak contribution (4%- 14%) of commercial banks in financing housing sector due to restriction of granting real estate finance. Moreover, political instability and miss- management of public resources have contributed to the failing of some economic and social projects. Nevertheless, Real Estate Commercial Bank (RECB) played a vital role in developing the housing sector through financing, constructing and rehabilitation of some housing projects. The study recommended to increase the capital of RECB and real estate financing ratio to enable it to provide housing and public services such as electricity, water stations and schools especially for people with low- income. Also, the state should take into consideration designing housing plans and banking policies that support housing sector to enable it to meet population growth.

BACKGROUND: Liver cirrhosis is one of common diseases that doctors deal with during working days, so it is important for all doctors to have a basic knowledge about its etiologies, clinical presentations, complications and prognosis. AIM OF THE STUDY: 1) To detect the most common causes of liver cirrhosis among Iraqi patients. 2) To Find the most common clinical presentations and look for any association between them and a particular etiology. 3) To make recommendations regarding screening for the most common etiology among population and deal with it and treat it early prior to development of liver fibrosis and cirrhosis. PATIENT & METHODS: A cross-sectional study was conducted from January 2016 to January 2019. 1000 patients were enrolled in the current study and followed at medical wards at Baghdad teaching hospital, taking detailed history from them including history of alcohol intake, drug history, etc... and sending them for complete work up including Abdominal US, virology screening, autoimmune, Wilson, iron study etc... and calculating Child - Pugh score for each patient. RESULTS: 1) The most common causes of liver cirrhosis are alcoholic liver disease (20%) and HCV (20%) followed by HBV (18%), NAFLD (14%), cryptogenic (14%), AIH (6%), Wilson (4%), PBC (4%). 2) the most common presentation of liver cirrhosis from all causes are ascites (38%) and encephalopathy (38%). followed by bleeding varices (21%), jaundice (11%). 3) HCV was associated significantly with Encephalopathy, NAFLD significantly associated with bleeding varices, Cryptogenic significantly associated with ascites, Wilson disease and PBC significantly associated with jaundice. CONCLUSIONS: HCV and alcoholism are so common among Iraqi patients with liver cirrhosis, while NAFLD cases are commonly related to diabetes mellitus and obesity. Ascites and encephalopathy are the most common presentation at medical wards from all causes of liver cirrhosis. Most cases of liver cirrhosis due to HCV are within middle and elderly. While Wilson disease should be kept at the top of differential diagnosis of liver cirrhosis among young individuals as it is significantly related to young age group. Cryptogenic cases of liver cirrhosis need aggressive work up and screening for uncommon causes.

Recent increases in the global demand for IT services have increased the power consumption, total ownership costs and environmental footprint of data centers. Recent efforts to reduce these effects have focused on either their cooling systems, or their power systems. In this paper, we have developed an integrated approach to minimize the total power demand of data centers, whilst their reliance on power imported from the grid is minimized. First, the power demand of data center has been reduced utilizing various air-side economizer-based cooling systems. Since the effectiveness of economizers significantly depends on the local weather conditions, 42 stations in major cities across the world have been considered. A more than 80% reduction in total cooling power consumption is achieved by using the most appropriate air-side economizer at each location. Second, the reliance of data centers on power imported from the grid is minimized utilizing on-site hybrid renewable power generation and energy storage. The on-site renewable power generation and capacity factors have been calculated for 1 MW wind and solar renewable power plants to identify the location with the highest renewable power generation capability. The optimal size of a hybrid renewable power plant, and associated battery energy storage system, is also determined for each data center using linear programming to minimize total levelized costs. Finally, the optimal location for constructing and operating the most energy efficient, cost-effective and sustainable data center has been identified by calculating its level of independence from the power grid. It is found that the level of grid independence increases as we move away from the equator, for example more than 50% grid independence can be achieved at Regina station located in Canada.

Energy storage systems have the potential to deliver value in multiple ways, and these must be traded off against one another. An operational strategy that aims to maximize the returned value of such a system can often be significantly improved with the use of forecasting — of demand, generation, and pricing — but consideration of battery degradation is important too. This paper proposes a stochastic dynamic programming approach to optimally operate an energy storage system across a receding horizon. The method operates an energy storage asset to deliver maximal lifetime value, by using available forecasts and by applying a multi-factor battery degradation model that takes into account operational impacts on system degradation. Applying the method to a dataset of a residential Australian customer base demonstrates that an optimally operated system returns a lifetime value which is 160% more, on average, than that of the same system operated using a set-point-based method applied in many settings today.

Antibiotic resistance is a worldwide public health emergency. Nonprescription antibiotic use is a chief cause of antibiotic resistance. The Saudi Government, as a consequence, imposed in 2018 executive regulations to prevent the distribution of antibiotics without a prescription. Herein, we aimed to investigate the prevalence of and risk factors for nonprescription antibiotic use among individuals presenting to one hospital in Saudi Arabia after enacting these regulations. This cross-sectional study was conducted on people, aged ≥18 years, who presented to the primary healthcare clinics of King Khalid University Hospital in Riyadh during the period between 1/1/2019 and 28/2/2019. Participants were asked to fill out a self-administrated questionnaire assessing their nonprescription antibiotic use during the past year in addition to sociodemographic information. Then, logistic regression analyses were performed to calculate the odds ratios (ORs) and corresponding 95% confidence intervals (CIs) for age, sex, education, and nationality of any nonprescription antibiotic use compared with no use within the past year. Out of 463 participants, 62.9% were females, 67.4% were &lt, 40 years, and 93.7% were Saudi citizens. Overall, 30.5% of participants reported nonprescription antibiotic use during the past year (19.7% one to two times and 10.8% more than two times). Male and non-Saudi participants were more likely to report any nonprescription antibiotic use, with HRs (95% CIs) of 1.99 (1.30, 3.04) and 3.81 (1.73, 8.35), respectively. The main reasons behind nonprescription antibiotic use were having previous experience with a health condition (69.2%), inaccessibility of healthcare (26.6%), and recommendation from a relative or a friend (16.1%). A major limitation of this study was that it included individuals attending one hospital. Individuals who seek medical consultation could be dissimilar to those who do not see doctors regarding nonprescription antibiotic use.

The economical operation of many distributed energy assets relies on effective on-line control, which in turn often requires forecasts to be made. To produce and evaluate forecasts, the error metric by which one measures forecast accuracy must be selected. A new method is presented which customizes a forecast error metric to a given on-line control problem instance, in order to improve the controller's performance. This method is applied to the real-time operation of a battery with the objective of minimizing the peak power drawn by an aggregation of customers over a billing period. In the empirical example considered, customizing the forecast error metric to each problem instance, improved performance by 45% on average, compared to a controller provided with a forecast of the same type, but trained to minimize mean-squared-error. Error metric customization is made possible by two newly proposed parametrized error metrics. The proposed method can be applied to any on-line optimization problem which requires a point forecast as an input, and which can be accurately simulated ahead of time. The method is likely to be most effective in applications where forecasting errors are quite high, as in these applications the choice of forecast error metric significantly affects the forecasts which are produced.

Our aim is to review the literature and, where appropriate, investigating subsequent antibiotic resistance in individuals prescribed antibiotics in primary care. Data sources are Observational and experimental studies identified through Medline, Embase, and Cochrane searches. Review methods Electronic searches using MeSH terms and text words identified 4373 papers. Results The review included 24 studies; 22 involved patients with symptomatic infection and two involved healthy volunteers; 19 were observational studies (of which two were prospective) and five were randomised trials. Conclusions Individuals prescribed an antibiotic in primary care for a respiratory or urinary infection develop bacterial resistance to that antibiotic.

BACKGROUND /AIMS: Colorectal cancer is the third most common cancer in 2018, the objective of our study was to describe the types and patterns of colorectal polyps in patients presenting to a tertiary care referral center in Baghdad. We also assessed the polyp detection rate (PDR) and adenoma detection rate (ADR). PATIENTS & METHODS: This is single-institution, descriptive cross-sectional study of consenting 103 patients who had colonoscopy done at the Endoscopy Unit of Baghdad teaching hospital, IRAQ from the 1st of June 2018 to 31st of March 2019 after taking verbal consent, The data collected included: Age, sex, Family history of colorectal malignancies and indication for the current colonoscopy. RESULTS: One thousand and thirty patients were included in the study with a mean age of 44 years (SD = 16), with 560 males representing 54.4% and 470 females representing 45.66%.The polyp detection rate in colonoscopies was 19.4% and the adenoma detection rate was 13.6%. Polyps were found and removed in 200 patients, 40% of the removed polyps were tubular adenomas, tubulovillous adenomas in 20%, villous adenomas in 10%, hyperplastic polyps in 5%. The majority of the polyps were in the distal colon in 80% of patients with polyps. CONCLUSIONS: The polyp detection rate was (19.4%) and adenoma detection rate was (13.6%). The majority of polyps were detected in distal colon.

Energy storage systems have a key role to play in increasing the uptake of distributed renewable energy generation. In many places, reduced feed-in tariffs and declining solar incentives are making behind-the-meter energy storage a favourable option for many distributed generation owners. Parts of the grid that have sufficient local generation can be operated as microgrids. In most cases, the temporal profiles of demand and generation do not align well, making energy storage design a critical step in proper microgrid design. Moreover, significant economic and operational benefits can be achieved by appropriately sizing and operating energy storage systems in microgrids. In this work we provide a framework that can be used for the sizing, positioning and operation of batteries in ways that both reduce the cost of operating a master-slave microgrid while also maintaining a high quality of service for the network. We formulate a mixed integer linear program based optimization algorithm that considers various operational and capital costs, as well as relevant network-related constraints. The performance of our algorithm is validated using a case-study simulation.

Much research is being conducted into the potential value of residential energy storage. The temporal resolution of the analyses carried out in these studies is typically driven by the available data, which is often only at 30-minute or 1-hour intervals. This study uses higher temporal resolution data to examine the effect of input time-series resolution on the value determined for residential storage. In the case study considered, an analysis carried out at a 30-minute interval underestimates the cost-saving delivered by 5kWh of residential energy storage by 17% on average, compared to the same battery analyzed at a 1-minute interval. The sensitivity of storage value to temporal resolution is found to vary significantly from one customer to the next. A method for improving estimates of the realtime value of energy storage using coarser time-series data is introduced. Finally the impact of temporal resolution on storage technology selection is also evaluated.

Distributed energy technologies, such as residential energy storage, embedded generation, and microgrids, are likely to play an increasing role in future energy systems. Getting the most value from these distributed assets is often dependent on the ability to optimize their operation in a distributed manner. This distributed optimization, in turn, calls for effective short-term forecasts of the output of small-scale generating assets, and the demand of small-scale aggregations of users. This paper introduces the integration of data-driven forecasting and operational optimization methods into a single model, avoiding the need to explicitly produce forecasts. The method is tested against two empirical energy storage operational optimization problems, the minimization of peak energy drawn by a small aggregation of customers, and the minimization of the energy costs of a collection of households which have rooftop PV systems. The integrated forecasting and operational optimization approach performs well at the peak demand minimization problem for intermediate-sized aggregations (50 residential customers or more), while an approach with separate forecasting and optimization performed better on the energy cost minimization problem. These results suggest that the integrated approach can be effective in applications where (i) forecasting difficulty is intermediate, and (ii) the exact operational optimization formulation can be well approximated by a data-driven model trained on a small fraction of the available forecast training data.

This paper presents and empirically evaluates two approaches to accounting for forecast uncertainty when attempting to optimize the operation of a residential battery energy storage system. Data-driven methods are used for forecasting, and dynamic programming, within a receding horizon controller, is used for operational optimization. The first method applies a discount factor to costs incurred at later intervals in a deterministic dynamic programming control horizon, provided with point forecasts. In the second approach probabilistic (scenario) forecasts are generated using Lloyd-Max quantization of the distribution of forecast errors, to allow the use of a stochastic dynamic programming formulation. These methods are applied to maximizing the cost-savings delivered from a residentially owned and operated battery, using a case-study of residential consumers with roof-top PV systems in New South Wales, Australia. It is found that scenario forecasts can offer an 8% increase in annual cost-savings, on average, when using a univariate multiple linear regression forecast.

BACKGROUND: Hepatitis C virus (HCV) infection is a serious public health problem in the world, and about 170 million patients are chronically infected with HCV. Worldwide; different epidemiologic patterns of HCV infection have been identified. AIM OF THE STUDY: By this study, we try to know the prevalence and risk factors for HCV transmission in Iraqi patients and genotype distribution of the disease. PATIENTS & METHODS: In a cross sectional study of 355898 persons, 232645 males & 123253 females; had been enrolled for the study in Baghdad teaching hospital, Iraqi blood bank, Al-Yarmouk teaching hospital, Al-Nu'man teaching Hospital and Al-Basrah teaching hospital from February 2017 to February 2019. Positive patients for hepatitis C antibody were further studied for way of transmission and viral load and genotype. History had been taken about the possible risk factor for HCV transmission which included (15) risk factors. RESULTS: A total of 355898 persons, 232645 males & 123253 females their Mean age at diagnosis was 47.3 (± 15.6) years, Ranged (19–78) years. The mean body mass index (BMI) of the study sample was 22.9 (± 3) kg/m2, studied all screen for hepatitis C antibody 1155 discovered to be positive 650 were males and 505 were females, further study done for viral load in 746 patients and genotype in 633 patients: 356 (48%) with high viral load, 390 (52%)with low viral load and 345 (52.8%) with genotype V and 301 (46.2%) with genotype IV, while genotype II was 2 (0.3%) and III 7 (0.5%), The most common possible ways of transmission of the disease by history in this study was blood transfusion 53%, dental procedure 42%, hemodialysis 36%, caesarean section 34.5%, while injured male during shaving 33%, patient who have surgical operation 24%, Tattooing in 8%, cupping in 6.6%, IV injection in 4% heterosexual seen in 2%, renal transplant in 2%, and only 1% in needle stick injury. while the more frequent genotype is 1 then 4. Hemodialysis and improper use of IV medication had been found to be more significant in HCV male patients .The relation between possible risk factor for transmission of HCV and residence, viral load were not significant. CONCLUSION: The most common probable risk factors as single risk factor for the male was blood transfusion, and for female was caesarean section. While for two risk factors for male were Blood transfusion and Hemodialysis and for female were Caesarean section & Dental procedure and for both gender were hemodialysis & dental procedure. While for three risk factors for both gender were surgery, barbers, and dental procedure. In our study we had found the prevalence of HCV in our Iraqi big sample was relatively low. The most common genotype was genotype I then genotype IV with rarity of genotype III 0 and genotype II.

Skin cancer is a group of heterogeneous malignancies, in general classified into nonmelanoma skin cancer (NMSC) and melanoma skin cancer (MSC). Incidences are high in many parts in the world with considerable geographical and racial variation. In the Yemen, there has been scarce information about skin cancer. The aim of this study was to evaluate the demographic characteristics and histological trend of skin cancer in Southern Governorates of Yemen.This retrospective study covered 204 cases of skin cancer at the Modern Histopathology Laboratory and Aden Cancer Registry and Research Center, Faculty of Medicine and Health Sciences, University of Aden, for the period 20062013. Data were classified regarding different demographic and tumor related variables and analyzed using CanReg4 for cancer registry and SPSS (version 21).The commonest encountered skin cancer was NMSC (93.1%). Generally, skin cancer appears slightly more frequently in females than males with a 1:1.06 male: female ratio, with a mean age of 62.9 years. Slightly higher than onethird (36.3%) were from Aden governorate. The head and neck proved to be the most common site in both males and females (58%). Basal cell carcinoma (BCC) is the most common histological type of skin cancer (50.5%).Skin cancer is a common cancer in patients living in southern governorates of Yemen. The pattern appears nearly similar to the international figures with a low incidence of MSC.

The purpose of this study was to perform an empirical investigation of the influence of select factors on the academic performance of students studying Principles of Financial Accounting (II). This study attempts to fill some of the gaps in the existing local and regional accounting education literature and to provide comparative evidence for the harmonization of international accounting education. A stepwise regression model using a sample of 205 students from the College of Business Studies, one of the tributaries of accounting education in Kuwait, was used to test the study’s hypotheses. The results indicate that the influences of the selected factors are diverse in their effects on student performance. The prerequisite grade had the most significant influence on student performance, followed by student GPA, time-lag (the time elapsed between studying the two parts of Principles of Financial Accounting), and finally college experience. Student gender, age, and major showed no significant influence on student performance. The study concludes by considering the implications of these findings for the administration of the College of Business Studies and similar institutions, and suggests avenues for future research.

The majority of renewable energy sources are non-dispatchable, meaning that it is not possible to control when and how much power they produce. For non-dispatchable renewable energy sources to meet a greater proportion of global electricity demand, the industry must develop and implement strategies that directly address the intermittency challenge. This paper considers electrical storage and transmission assets as alternative means of matching non-dispatchable generation with non-deferrable demand. It seeks an optimal combination of storage and transmission assets for a simplified representation of Australian population centres, assuming that demand is met entirely with solar PV generation. This problem is solved using a Mixed Integer Linear Program. Under the baseline assumptions it is found that the optimal (lowest cost) solution has significant quantities of storage in all load centres, as well as transmission assets installed over large distances. The storage selected was 10–15% Li-ion batteries by energy; with the remainder being pumped hydro storage.

Objectives: The aim of the study was to know the sero-plevalence of Herpes Simplex Virus (HSV) infection in pregnant women attending a university hospital in Sudan. Methods: All pregnant women who came for delivery by lower segment caesarean section (LSCS) in National ribat teaching hospital between May and November 2011 were enrolled in this study. Their blood was tested for HSV IgG & IgM immunoglobulin. Their vulvas were examined for eruptions and ulcers and when those were found surface swabs were taken for isolation of organisms including syphilis. Their blood was also tested for HIV and syphilis. Results: One hundred thirty pregnant women were included in the study and forty five women (34.6%) tested positive for the IgG of Herpes virus but none of them was positive for the IgM test. Fourteen women had genital rashes/ulcers and nine of them tested positive for IgG but not IgM. Eleven women had lip ulcers or blisters and five of them tested positive for herpes. Conclusion: Acute infection during pregnancy was not documented in this study population and probably women develop immunity to herpes virus early in their reproductive life. Genital rashes and ulcers were not associated with active herpes infection.