Dalanj University

Background: War has far-reaching consequences for individuals, communities, governments, and even global systems. Civilians in Sudan have suffered serious and frequently targeted wounds and other suffering during the war. A collapsed health system, a lack of medical supplies, and purposeful attacks on healthcare facilities make it impossible for wounded individuals to receive care. As a result, the purpose of this study was to determine the relationship between the injurious site and the demographic characteristics of injured people during the Sudan war of 2023–2024. Methodology: This is a prospective descriptive analysis conducted at El-Obeid Teaching Hospital from May 2023 to May 2024. The study encompassed all civilian casualties resulting from the armed conflict who were admitted to El-Obeid Teaching Hospital in El-Obeid, North Kordofan State, Sudan. Results: The majority of participants were aged 18-24 years, followed by those under 18 and aged 25-34 years, accounting for 26%, 20.5%, and 17.5%, respectively. In terms of occupation, the majority of the wounded were self-employed, comprising 48.5%, followed by students at 13% and pupils at 10.5%. The most prevalent sites are the lower limbs, followed by the upper limbs, abdomen, and chest, comprising 46.5%, 25.5%, 25.5%, and 19%, respectively. Conclusion: The primary body sites impacted during armed conflict include the lower and upper extremities, as well as the abdomen. Individuals engaged in outdoor occupations and students experience the highest rates of injury.

An online gradient method is the simplest and most widely used training method for feed forward neural networks (FFNNs). However, a problem can arise with this method: sometimes the weights become very large, leading to overfitting. Regularization is a technique used to improve the generalization performance and prevent overfitting in networks. This paper focused on the convergence analysis of an online gradient method with L1 regularization for training FFNNs. L1 regularization promotes sparse models but complicates the convergence analysis process due to the inclusion of the absolute value function, which is not differentiable. To address this issue, an adaptive smoothing function was introduced into the error function to replace the L1 regularization term at the origin. This approach encourages a sparser network structure by forcing weights to become smaller during training and eventually eliminating them after training. This strategy simplifies the network structure and accelerates convergence, as demonstrated by the numerical experiments presented in this paper. Additionally, it enables us to prove the convergence of the proposed training method. Numerical experiments based on 4bit and 5-bit parity problems, Gaussian and hyperbolic function approximations, and Monk and Sonar classifications are provided to validate the theoretical findings and the superiority of the proposed algorithm.

Following publication of the original article [1], the author name "Fatema Suliman Alatawi" was incorrectly written as "Suliman Alatawi". This has been corrected with this erratum. The original article has also been corrected.

Since December 2019, an outbreak of severe respiratory infection (COVID-19) emerged in the city of Wuhan in China. The knowledge, awareness and practice of medical students toward COVID-19 pandemic is of most importance as it demonstrates their preparedness to deal with this pandemic. The objective of this study is to assess the knowledge, awareness and practice of medical students in Sudan universities about COVID 19. This is a cross-sectional study conducted on 19 universities that have medical schools in Sudan. Data from at least 100 medical students from each university were included in the study. Data were collected using an online questionnaire in April 2020. Statistical analysis was conducted using the Statistical Package for Social Science software, version 25. About 2603 medical students from 19 universities were included. Overall good knowledge and practice were demonstrated by the medical students (88.9%) and (78.6%), respectively. Respondents who answered that the most common clinical symptoms of COVID-19 were the main combination of dry cough, fatigue and fever were (27.7%), and the first initial symptom was headache were (48.3%.). (60.2%) Wear medical masks, (95%) said that avoiding crowded places protects against the spread of COVID-19, and (50.7%) have confidence that Sudan can win the battle against the COVID-19. Finally, (68.8%) agreed that COVID-19 will finally be successfully controlled. This study has found that medical students in Sudan demonstrated good knowledge and good practice toward Covid19.

This study was aimed to assess the antibacterial and antifungal activities of Balanites aegyptiaca seed oil and characterize the physicochemical properties. Seeds were collected from the local central market, Khartoum-Sudan (2019). The samples were dried under shade and grinded, then the oil was extracted with a Soxhlet extractor using n-hexane. The percentage yield of the extract was found to be 25.64%. The seed oil was tested against Pseudomonas aeruginosa (G-), Escherichia coli (G-), Bacillus subtilis (G+), Staphylococcus aureus (G+), and Candida albicans to assess their antimicrobial properties. The extract of B. aegyptiaca seed oil has antimicrobial activity against most of the organisms tested. The fatty acid profile of the B. aegyptiaca seed oil was analyzed by GC/MS. The results revealed that the presence of five fatty acids, including saturated linoleic acid, oleic acid, and unsaturated palmate and stearic acids, also a unique antioxidant compound butylated hydroxytoluene. The physiochemical properties of the seed oil showed that the oil contained kinetic viscosity (57 cp), density (0.917 g/cm3), refractive index (1.472), acid value (49.96 mg/kg), saponification value (248.75 mg/g), ester number (234.79 mg/kg) and peroxide number (0.02 mg/kg). Through physiochemical analysis, it was found that oil can be used for human consumption due to the percentage yield of unsaturated acids (81%). In addition, the results of the antioxidant activity of the seeds oil showed that the seed oil had moderate antioxidant activity.

This study was designed to determine the effects of deep litter floor and battery cages housing system on layer feed consumption and egg production rate. Thirty two commercial hybrid layers (hyline) of 10 months production age were randomly selected and distributed equally in four deep litter ground cages, and thirty (hyline) layers were kept in battery cages, which consisted of triple deck cages, provided with automatic nipple watering system and front trough feeders. During the experimental period there were slight changes in live body weight, it was about -0.01 kg in deep litter and about 0.04 kg in battery cages system. Layers housed in deep litter system significantly consumed more feed compared to that kept in battery cages except at first week, and best averages of feed conversion ratios were calculated for layers housed in deep litter than that kept in battery cages, differences were significant for second, third, fourth and fifth weeks of experimental period. Egg production rate were significantly different in layers housed in deep litter system through the production period except the first weeks.

Let , with , be a homogeneous function of degree zero. In this paper, we establish the boundedness of the homogeneous fractional integral operator on weighted Herz spaces with variable exponent .

Abstract In this research, the results of radon concentration, surface and mass exhalation rates, radium concentration, effective dose rate and the alpha index have been investigated in a number of 198 soil samples that have been collected from various residential locations of Halfa Aljadida area, Sudan. The can technique, containing CR-39 have been used. From our results, the average value of soil gas radon concentration was found to be 1.96±0.22 kBq·m−3. The average values of surface and mass exhalation rates were 1.73±0.19 Bq·m−2·h−1 and 34.79±3.87 mBq·kg−1·h−1, respectively. The radium concentration average value was 8.06±0.90 Bq·kg−1. While the average value of the effective dose rate was recorded to be 54.69±6.11 mSv·y−1. The average value of alpha index of studied samples was (4.03±0.45)×10−2. From the study, a good positive and linear correlation between radium concentration, surface and mass exhalation rates of soil samples were present. In addition to that, a positive and linear correlation between radium and radon concentrations was found. Finally, a comparison between the results and other findings was conducted and the results imply the fact that the area under consideration is safe as if the health hazard are mentioned.

Acacia senegal (locally: Hashab tree) is one of the most important tree species in Sudan as it considers the main Gum Arabic producing tree. The objective of this study is to investigate the socio-economic aspects of gum Arabic production and to assess contribution of gum Arabic to sustainable livelihood of local people in Dalanj Locality, South Kordofan State-Sudan. Social survey was carried out by using structured questionnaire for 80 respondents (gum producers) on random sample basis in eight villages, 10 respondents from each village. Issues pertaining to socio-economic factors affecting gum Arabic production and contribution of gum Arabic to sustainable livelihood of local people, in Dalanj Locality, were assessed. Results of the study revealed that expansion of agriculture lands at the expense of hashab trees, fires and illegal felling are the most important factors constraining gum production in the area. The results also indicated that agriculture is the main source of income and gum Arabic is a supplementary source of income. The importance of gum Arabic becomes apparent during (off farm season) the period between crops harvest and the preparation of the next agricultural season. Establishment of producers' associations and provision of loans to producers are highly recommended to ensure sustainability of gum production.