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Introduction: Vaccine hesitancy is undermining individual and community protection from vaccine-preventable diseases. This study aimed to investigate the level of awareness and perception of the COVID-19 vaccine and its determinants among people in Wad Madani City, Gezira State, as well as its known side effects. Methods and Results: This cross-sectional, descriptive, and correlative study included 400 participants (56.8% females and 43.2% males) who visited Wad Madani neighborhood COVID-19 centers during the data collection period (June 2022). The data was collected using a structured questionnaire based on prior published studies. Approximately 93.0% of the participants knew the importance of the COVID-19 vaccines, 84.8% knew about their effectiveness, and 83.8% knew that the vaccines help to reduce the risk of virus infection. However, only 58.0% were vaccinated against COVID-19. The results showed that 56.8% of the participants did not develop side effects. Among those who did, the most common side effects were headache and fever (10.2%), injection site pain (7.9%), myalgia (7.1%), and chills and swelling (5.6%). The results showed that 52.5% had negative perceptions of the COVID-19 vaccines. Urban residents were 2.17 times more likely to have a positive perception of the COVID-19 vaccine than rural residents (P=0.05). Furthermore, study participants with nuclear family type have shown a positive attitude toward the COVID-19 vaccines and were 2.32 times more likely to have had a positive attitude than participants with extended family (P=0.036). Moreover, participants not vaccinated were found to be less likely to have had a positive attitude toward the COVID-19 vaccine, when compared with vaccinated participants (P= 0.005). Conclusion: Although society is aware of the need for COVID-19 immunization, the community has a low positive perception toward COVID-19 vaccination. Similarly, people in rural areas are less aware of the significance of immunization. Local health officials must collaborate to address public fears about vaccinations through the media.

Gastrointestinal cancers are a huge worldwide health concern, which includes a wide variety of digestive tract cancers. Circular RNAs (circRNAs), a kind of non-coding RNA (ncRNAs), are a family of single-stranded, covalently closed RNAs that have become recognized as crucial gene expression regulators, having an impact on several cellular functions in cancer biology. The gut microbiome, which consists of several different bacteria, actively contributes to the regulation of host immunity, inflammation, and metabolism. CircRNAs and the gut microbiome interact significantly to greatly affect the growth of GI cancer. Several studies focus on the complex functions of circRNAs and the gut microbiota in GI cancers, including esophageal cancer, colorectal cancer, gastric cancer, hepatocellular cancer, and pancreatic cancer. It also emphasizes how changed circRNA expression profiles and gut microbiota affect pathways connected to malignancy as well as how circRNAs affect hallmarks of gastrointestinal cancers. Furthermore, circRNAs and gut microbiota have been recommended as biological markers for therapeutic targets as well as diagnostic and prognostic purposes. Targeting circRNAs and the gut microbiota for the treatment of gastrointestinal cancers is also being continued to study. Despite significant initiatives, the connection between circRNAs and the gut microbiota and the emergence of gastrointestinal cancers remains poorly understood. In this study, we will go over the most recent studies to emphasize the key roles of circRNAs and gut microbiota in gastrointestinal cancer progression and therapeutic options. In order to create effective therapies and plan for the future gastrointestinal therapy, it is important to comprehend the functions and mechanisms of circRNAs and the gut microbiota.

Colorectal cancer (CRC) is ranked as the world's third-most prevalent cancer, and metastatic CRC considerably increases cancer-related fatalities globally. A number of complex mechanisms that are strictly controlled at the molecular level are involved in metastasis, which is the primary reason for death in people with CRC. Recently, it has become clear that exosomes, which are small extracellular vesicles released by non-tumorous and tumorigenic cells, play a critical role as communication mediators among tumor microenvironment (TME). To facilitate communication between the TME and cancer cells, non-coding RNAs (ncRNAs) play a crucial role and are recognized as potent regulators of gene expression and cellular processes, such as metastasis and drug resistance. NcRNAs are now recognized as potent regulators of gene expression and many hallmarks of cancer, including metastasis. Exosomal ncRNAs, like miRNAs, circRNAs, and lncRNAs, have been demonstrated to influence a number of cellular mechanisms that contribute to CRC metastasis. However, the molecular mechanisms that link exosomal ncRNAs with CRC metastasis are not well understood. This review highlights the essential roles that exosomal ncRNAs play in the progression of CRC metastatic disease and explores the therapeutic choices that are open to patients who have CRC metastases. However, exosomal ncRNA treatment strategy development is still in its early phases; consequently, additional investigation is required to improve delivery methods and find novel therapeutic targets as well as confirm the effectiveness and safety of these therapies in preclinical and clinical contexts.

Objectives: Type 1 diabetes mellitus is a chronic autoimmune disease caused by insufficient production of insulin. Many studies have linked type 1 diabetes mellitus to vitamin D 3 deficiency. We investigated the prevalence of vitamin D deficiency in Sudanese children and adolescents with type 1 diabetes mellitus and assessed the impact of vitamin D deficiency treatment on their glycemic control. Methods: In 2019–2022, we conducted a quasi-experimental study on 115 children with type 1 diabetes mellitus (1–19 years old) at the Sudan Childhood Diabetes Center. Vitamin D supplements were given orally to deficient patients for 3 months. The concentrations of hemoglobin A1c, fasting blood glucose, insulin dosage, and vitamin D (25-hydroxyvitamin D (25(OH)D)) were measured before and after vitamin D3 administration. One-way ANOVA and paired sample t- tests were used to evaluate the effect of supplementation. Results: Only 27% of type 1 diabetes mellitus children were deficient in vitamin D, whereas 31.1% were inadequate and 40.9% were sufficient. The administration of vitamin D supplements slightly improved hemoglobin A1c levels in 67.7% of the patients, but the difference was not significant (mean 10.8 ± 2.1% before, 10.1 ± 2.5% after, p 0.05 = 0.199). However, there was a significant decrease in the fasting blood glucose level (mean: 174.978.5–136.759.1 ng/ml; p 0.05 = 0.049). Vitamin D levels were significantly increased after treatment (mean = 49.6 ng/mL; t- test = −11.6, 95% CI 40.8–(−28.6); p 0.05 = 0.000). After vitamin D3 supplementation, 25.8% of individuals changed their insulin dosage; however, there was no significant variation in insulin needs. Conclusions: The prevalence of vitamin D deficiency in children and adolescents with type 1 diabetes mellitus in Sudan is relatively high; incorporating vitamin D supplements in their treatment plan may improve their glycemic control.

In order to reduce the default rate of corporate bond market, the author proposes to use digital signal processing and multiple regression analysis to study the prediction system of financial distressed companies. First, design the research method, Logistic regression model is the most commonly used multivariate statistical method when modeling binary dependent variables, it can solve the problem of nonlinear classification, it has no specific requirements for the distribution of variables, and the accuracy of judgment is high. The author selects 32 financial ratios from the perspectives of solvency, operating ability, profitability, development ability, per share index, and risk level. Taking special treatment (ST) due to abnormal financial status as a sign of financial distress in listed companies, when selecting samples, the matching principle is adopted to select non-ST companies as matching samples. Two methods of logistic regression and support vector machine are used for empirical testing, and both in-sample testing and out-of-sample prediction are performed. The results show that when using the logistic regression method, the propensity to default indicator (TTD) reflected in the text content, it can indeed improve the out-of-sample prediction accuracy of the financial distress prediction model, and it is consistent with the in-sample test, this is mainly reflected in the reduction of the first type of error, that is, the probability of misjudging a financially distressed company as a normal company. Changes in the proportions have little effect on the relative importance of financial ratio variables when modeling with support vector machines, the propensity to default indicator (TTD) entered the top ten important variables in both ratios, and ranked fourth among all indicators when the ratio was 1:2, importance has increased significantly. From this it can be seen that, when using support vector machine to build a financial distress prediction model, the propensity to default indicator (TTD) has played an important role. In the case of using the support vector machine method, adding the default tendency indicator (TTD) reflected by the text information can also improve the accuracy of the financial distress prediction model.

According to the needs of higher education teaching evaluation, we analyzes the problems in teaching evaluation, provide the method of using accompanying data acquisition and mathematical analysis, designs the education and teaching big data platform, collects the relevant data generated in the teaching process in real time by using information system, video equipment and IoT system, optimizes the evaluation indicators, and constructs the evaluation model, achieve comprehensive evaluation in objectively and real time.

College students can improve their physical fitness through sports activities. But physical activity requires long-term persistence. In this way, college students are required to carry out self-control. This paper studies the relationship between college students’ physical exercise motivation and self-control ability by using the mathematical model of probability theory. We use probabilistic path analysis to test the fit and difference of the relationship between the two. At the same time, the article uses Lyapunov’s characteristic function method to prove the correlation between physical exercise motivation and self-control ability again. The results show that the algorithm proposed in this paper can improve the self-management efficiency of college students.

In the context of information construction, faced with a large number of network information data, in order to obtain more valuable information in an effective time, researchers put forward a recommendation algorithm for information explosion. Because the recommendation algorithm has been successfully applied in many fields such as business, the relevant algorithm system has also begun to be fully implemented in the field of books. There are many kinds of recommendation algorithms, among which collaborative filtering recommendation technology is the most widely used. Therefore, based on the humanized library service concept, this paper mainly studies the influencing factors of reader satisfaction, and on the basis of constructing multiple linear regression model, clarifies the practical significance of constructing collaborative filtering personalized recommendation system for libraries. Then, an improved clustering algorithm is proposed to reduce the dimensionality of the original matrix, and an empirical analysis is made on the book collaborative filtering personalized recommendation system based on linear regression equation by using the operation idea of calculating the score according to the borrowing time. The final results show that, according to the multiple linear regression model between reader satisfaction and its influencing factors, in order to improve library service quality and build a good learning and reading environment, collaborative filtering algorithm should be combined to build a personalized book recommendation system, and this system is feasible in practical application..

This article uses SPSS19.0 and AMOS21.0 statistical software to explore the relationship between corporate talent management and corporate performance. We use the structural equation model to quantitatively analyze the human resource management factors that affect logistics performance. Research shows that intellectual capital has a significant positive effect on enterprise innovation performance. The value proposition of employee training to customers and good customer service have an overall positive economic effect. Human capital plays a significant role in driving innovation performance only in the more mature stage of enterprise development.

The article applies mathematical statistics to the dynamic analysis of the demand for talents in large companies. Prediction of the overall demand for talents through the use of deep learning models. We use the theory of diminishing marginal utility to solve the degree of enterprise human resource investment under each index. Based on the analysis of traditional human resource management methods, this paper uses the three-dimensional fuzzy model to construct a new three-dimensional fuzzy model of human resource management model. The research found that the algorithm proposed in this paper can improve the quality of data training and improve the matching of people and posts.

Patient blood management (PBM) is a comprehensive approach to optimizing the care of patients who might need a transfusion. It involves the use of evidence-based strategies to reduce or avoid the need for allogeneic blood transfusions while ensuring that patients receive safe and appropriate care. PBM includes strategies such as preoperative autologous donation, intraoperative cell salvage, and minimally invasive techniques to reduce bleeding. The purpose of this study is to assess the medical staff’s awareness of preoperative PBM in Saudi Arabia. Between April 2022 and July 2022, data was collected using a 10-minute online (Google Forms) self-administered, anonymous, researcherstructured questionnaire adapted from previous studies and translated into both English and Arabic. The questionnaire was divided into three sections. The first section contained sociodemographic data, while the second section was used to estimate physicians’ and nurses’ knowledge of preoperative PBM. Two questions in Part 3 of the questionnaire were used to assess doctors’ and nurses’ preoperative PBM attitudes and practices. The average relationship between patients’ blood management attitudes and levels of awareness. It was revealed that there was a positive attitude (P≤0.005) as well as a high level of awareness (P≤0.002). The effect of job, gender, or geographical distribution on PBM awareness, attitude, and practice was not significant. Despite the fact that the majority of participants have a positive attitude and good awareness of PBM, more efforts should be implemented to improve PBM awareness, which was linked to increased transfusion practices and lower product costs.

The goal of phishing assaults is to trick users into giving up personal information by making them believe they need to act quickly on critical information. The creation of efficient solutions, such as phishing attack detection systems backed by AI, is essential for the safety of users. This research suggests a two-stage hybrid strategy that uses both URL and content analysis to identify phishing assaults. In the first step of the suggested method, URL analysis is used to determine the legitimacy of suspected phishing assaults. If the site is still live, the second check uses content analysis to determine how serious the attack is. Both analysis' findings are taken into account in the decision-making procedure. As can be seen from the experiments, the hybrid system obtains an astounding 99.06% accuracy rate. This research adds to the existing body of knowledge by providing a massive dataset of over 14 million data samples that includes both legal and phishing URLs. Furthermore, when content analysis is required for phishing URL detection, the two-stage hybrid technique significantly outperforms URL analysis alone by 70.23 %. The proposed method provides better defense against phishing attempts and is practical enough for widespread use.

The purpose of this study was to evaluate the anticoagulant activity of Thymus atlanticus leaves. Methods and Results: This cross-sectional study was carried out in Khartoum state from March 2021 to June 2021. This study comprised 60 healthy volunteers (40% men and 60% women) aged 19-25 years. Activated partial thromboplastin time (APTT) and prothrombin time (PT) were evaluated in the blood plasma with different amounts of Thymus atlanticus leaves using Coatron M1 (TECO Medical Devices). Thymus atlanticus leaves considerably lengthened APTT and PT in all tested concentrations. Furthermore, only the APTT test at a concentration of 5.17 μl revealed a significant difference in the anticoagulant activity of Thymus atlanticus leaves between males and females. No correlation between age and anticoagulant activity of Thymus atlanticus leaves on PT and APTT in the study was found.

Modern optimisation is increasingly relying on meta-heuristic methods. This study presents a new meta-heuristic optimisation algorithm called Eurasian oystercatcher optimiser (EOO). The EOO algorithm mimics food behaviour of Eurasian oystercatcher (EO) in searching for mussels. In EOO, each bird (solution) in the population acts as a search agent. The EO changes the candidate mussel according to the best solutions to finally eat the best mussel (optimal result). A balance must be achieved among the size, calories, and energy of mussels. The proposed algorithm is benchmarked on 58 test functions of three phases (unimodal, multimodal, and fixed-diminution multimodal) and compared with several important algorithms as follows: particle swarm optimiser, grey wolf optimiser, biogeography based optimisation, gravitational search algorithm, and artificial bee colony. Finally, the results of the test functions prove that the proposed algorithm is able to provide very competitive results in terms of improved exploration and exploitation balances and local optima avoidance.

Abstract: Background: Breast cancer is the most frequent cancer in women globally as well asSudan, it has risen to become the second commonest cause of death in women.Vitamin D receptor (VDR) is a ligand-dependent transcription factor. Vitamin D-ligandedVDR, has anti-proliferative properties in a variety of tumor types by inducing cell cycle arrest, senescence, differentiation, and death. The role of VDR TaqI polymorphism is currently unknown. However, studies suggest that these polymorphisms may affect messenger RNA (mRNA) stability. Methods and patients: This case control 198 participants, (97) breast cancer patients and another 101control group. Data was collectedby a questionnaire. 2 ml of venous blood was collected and stored at -20 till DNA extraction. Phenol chloroform method was used for DNA extraction. VDR TaqI was examined and genotyped using CTPP-PCR after designing of suitable primers and PCR condition. Then data was analyzed statistically using the SPSS program (version 21) and the SNPS tats online tool. Results: The three genotypes reported in this study for TaqI SNP (CC, TC, and TT) were evenly distributed throughout cases and controls, so according to this findings there is no statistically significant association of this SNP with breast cancer risk (p. value 0.650) (OR(95%CI) 1.39 (0.64-3.00), 1.00 (0.54-1.87), 1.00). Conclusions: This study found no association of TaqI polymorphism and breast cancer risk factors

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Theoretically, several self-tuning control (STC) algorithms have been developed and many simulation results have proved their feasibility in the past years, but applications of STC are hardly seen. This paper proposes direct and indirect STC plans that can be applied to a chemical process system with a time delay auto-regressive and exogenous model of a varied time constant. The plan controller is a combination of a generalized minimum variance control (GMVC) strategy and an identification algorithm (simplified parameter) called recursive least squares to estimate controller parameters for the direct method and plan parameters for the indirect method. The experimental results show that GMVC is able to track the desired input or set point.

Background and objective: Renal failure is a worldwide public health concern due to the significant increase of patients each year. Diet and nutrition play a crucial role in symptom management, quality of life and survival of renal failure patients, as well as the prevention of disease progression. This study aimed to assess nurses’ knowledge of the nutritional management of patients with renal failure and to find out the relationship between nurses’ knowledge and their socio-demographic characteristics. Methods: A descriptive cross-sectional research design was used from April to August 2016. A purposive sample of 51 nurses at the Dialysis Unit of Hawler Teaching Hospital and Hawler Dialysis Center, Kurdistan Region, Iraq were recruited and completed a self-reported questionnaire. Results: Most participating nurses were male (76.5%), and the majority (52.9%) were between 26-32 years old . Most of them were married (68.6%), had a diploma certificate (58.7%) with 37.3% having 4-7 years of working experience at the two above-noted dialysis centers. The majority of nurses (70.6%) had fair knowledge score, while 17.6% had a good knowledge score and 11.8% had a low knowledge score. Conclusion: The majority of nurses had fair knowledge regarding nutritional management for renal failure patients.

Backgrounds and objective: Heart failure is a major public health problem in the world with a significant load of disease on population and the individual, this burden of disease can be measured in terms of mortality, readmission rate, and healthcare costs. Adequate knowledge about the disease is an effective strategy to prevent further disease complication. The study aimed to determine the effect of a health education program on heart failure patients regarding their disease through a pre-post-test approach. Methods: A quasi-experimental study with the application of pre and post-test approach for both the study and control group at Hawler Teaching Hospital, Rizgary Teaching Hospital and Rojhalat Hospital on patients with heart failure. A non-probability purposive sampling technique used on 400 heart failure patients chosen to include in the study. The study samples were divided into two groups; 200 patients as a study group and exposed to the health education program, and the other 200 patients were not exposed to the health education program and considered as the control group. The measurement of the effectiveness of a health education program through the knowledge assessment includes six main domains like General information, risk factors, causes, clinical manifestation, diagnosis, and management of heart failure. Statistical data analysis achieved through descriptive and inferential data analysis. Results: The results indicated that a health education program was effective among patients regarding management heart failure. It also indicates that there is good improvement with highly significant differences in study group between pre and post-test, in over-all items. Conclusion: The study concluded that the educational program is an appropriate and effective way to improve the patient's knowledge about heart failure.

Background and objectives: Chronic obstructive pulmonary disease (COPD) has been reported as the most common cause of morbidity and mortality all over the world. The present study aimed to investigate a possible link between chronic obstructive pulmonary dis-ease and increased risk of cardiovascular disease in Erbil, the Kurdistan Region of Iraq. Methods: A quantitative, case-control study was conducted on 159 patients with COPD as the case group and 159 adult people without COPD as control group. Case groups were patients who have COPD and admitted to the medical ward at Hawler Teaching Hospital and Rzgary Teaching Hospital. Control groups were those without COPD and went to City Park and Mala-fandy Primary Health Center. Data was collected from January 2018 to August 2018 through direct interview and using a questionnaire. A spirometer machine was used to confirm the diagnosis of COPD. Data analysis was carried out through descriptive statistics (frequency and percentage), skeunosis-kurtosis test, t-test, Mann-Whitney U test, Pearson's Chi-squared test, and univariate logistic regression. Results: Compared to the control group, patients with chronic obstructive pulmonary dis-ease were found to be at a significantly higher risk of developing hypertension, diabetes, ischemic heart disease, dyslipidemia, and lung cancer. Moreover, there was an inverse correlation between increased severity of chronic obstructive pulmonary disease and in-creased hypertension and stroke. In addition, chronic obstructive pulmonary disease, hypertension, diabetes, and dyslipidemia were found to be significant risk factors for ischemic heart disease. Conclusions: The risk of cardiovascular comorbidities was significantly higher in the patients with chronic obstructive pulmonary disease and there is a significant association between chronic obstructive pulmonary disease and cardiovascular comorbidities.

Background and objectives: Heart Failure is a common and significant health problem, with an increasing incidence and a gloomy prognosis that is often accompanied by a negative impact on the length and quality of life of patients. This study aimed to assess quality of life among patients with heart failure in Erbil city and to find the association of quality of life domains (physical, level of independence and social relationship) with some socio-demographic data (age, gender, level of education, and marital status) Methods: A quantitative design / a descriptive cross-sectional study was conducted at Hawler and Rizgary Teaching Hospitals in Erbil city Kurdistan region. This study was carried out from November 17th 2014 to November 17th 2015 on non-probability (purposive) samples was selected among 140 heart failure patients who were admitted to coronary care unit and medical ward of both teaching hospitals. Their quality of life was measured by standardized questionnaire of world health organization with some modification. Results: The findings of the study indicated that most patients were Female and Illiterate, their mean age was 68.75. Moreover, significant associations exist between levels of education with physical ability, level of independence, social domains, and marital state with physical domain. Conclusion: The study concluded that the majority of the study sample had moderate level of quality of life while less than one-fourth of them had poor level.

Background and objective: The effect of physical activity and diet is an essential modifiable or environmental factor. Evidence from epidemiological studies suggests that assessing associations between diet and general health is important. The aim of the study was to assess the level of physical activity and fat-related eating behaviour of patients with cholelithiasis. Methods: A matched case-control study was done on 100 participants; 50 were patients with gallstone disease and 50 were patients without gallstone disease. The study was conducted from December 2017 to June 2018. The constructed questionnaire used and designed based on the literature review. It consisted of four parts: demographic data, physical activity, fat-related eating behaviour, and investigations. Ultrasounds were done on all study participants to confirm whether patients had gallstone disease or not. Reliability of the questionnaire was determined through a pilot study and the validity through a panel of experts from medicine and nursing fields. Frequency, percentage, mean and standard deviation, and the chi-square test was used for analyzing data. Results: In total, 70 female and 30 male patients were investigated. Most (52%) were 28 to 47 years old. Most (72%) were physically inactive. Regarding fat-related eating behaviour most (73%) had unhealthy behavior. There was a significant association between physical activity and the risk of getting cholelithiasis. Risk of disease the development was about 2.8 times higher in patients who were physically inactive (odds ratio = 2.79, 95% CI; 1.1–7.0) in comparison to patients were physically active. There was no significant difference between development of cholelithiasis and unhealthy fat-related eating behaviour (odds ratio = 0.886, 95% CI; 0.338–2.323). Conclusion: There is a significant relationship between cholelithiasis and engaging in physical activity.

Thirteen simply supported steel samples have been tested to explain the effects of strengthening steel beams using an external prestressing strand. The samples have the same cross-sectional dimensions and overall length. One steel beam without strengthening was taken as a reference, while the other twelve of them had been strengthening by two external strands at various eccentricity locations and jacking stresses. The strengthening by external prestressing strands is sub-divided into two series according to jacking stress. Each series consists of six steel samples divided according to the eccentricity location of prestressing strand. During tests, it was found that the Load deflection response for the strengthened samples is stiffer as compared with the reference. The increasing percentage in ultimate load capacity was increased to 0.347, 2.758, 3.921, 8.898, 9.326, and 10.256% for beams under jacking stress of 1120 MPa, while increasing percentage in ultimate load capacity were increased to 0.17, 26, 33, 48.5, 13.7, and 69.56% for beams under jacking stress of 815 MPa. On the other hand, the maximum percentages of deflection were decreased to 4.88, 2.44, 20.62, 15, and 9.7% when the jacking stress increase from 815 to 1120 MPa and the ratio of the quarter to mid-span deflection (δ quarter / δ mid) is about 0.528 and 0.497 when jacking stress is 1120 and 815 MPa respectively. So, the increase in jacking stresses from 815 to 1120 MPa will not be preferable because it has a little increasing percentage in stiffening and behaviors compared with other tested beams at the same condition.

Abstract Background Malaria is the leading cause of morbidity and mortality in Sudan. The entire population is at risk of contracting malaria to different levels. This study aimed to assess the effectiveness of communication for behavioural impact (COMBI) strategy in enhancing the utilization of long-lasting insecticidal nets (LLINs) among mothers of under-five children in rural areas. Methods A randomized community trial was conducted in rural area of Kosti locality, White Nile State, Sudan, among mothers of under-five children, from January 2013 to February 2014. A total of 761 mothers from 12 villages were randomly selected, 412 mothers from intervention villages and 349 were from comparison villages. Results The knowledge of mothers, in intervention villages, about malaria vector, personal protective measures (PPM) against malaria, and efficacy of LLINs was significantly increased from 86.9 to 97.3 %; 45.9 to 92 % and 77.7 to 96.1 % respectively. Knowledge about usefulness of PPM, types of mosquito nets and efficacy of LLINs was significantly higher in intervention villages compared to comparison villages (p

INTRODUCTION: medical students are the source of a country's physicians. Determining how medical students select their areas of specialization is the key to achieve a balanced distribution of doctors among all specialties. The objective is to identify the number of medical students who have decided their postgraduate specialty career, their career specialties preference, and factors that may influence their decision to select a particular specialty. METHODS: a facility based cross-sectional study was conducted in September 2013 at Faculty of Medicine, University of Medical Sciences and Technology, Khartoum, Sudan. A self-administered semi-structured questionnaire comprising demographic data and questions about future specialties preferences and factors influencing those preferences was distributed to 887 male and female students, (from first to fifth academic years) recruited in the study. RESULTS: response rate was 73% with 647 questionnaires collected, out of 887 eligible medical students. Of the returned questionnaires, 604 were valid. The majority of students (541, 89.6%) have chosen a specialty. Surgery, medicine, paediatrics and obstetrics and gynecology were the most selected specialties. The least selected specialty was anaesthesiology. A significant association was found between gender and specialty choice using Chi-square test (p=0.00). There was no association between undergraduate level and specialty choice (p=0.633). The most common reason for choosing a specific specialty was "Personal Interest" (215, 39.7 %) followed by being "Helpful to the community" (144, 26.6%). CONCLUSION: surgery, medicine, paediatrics and obstetrics and gynecology were the most selected specialties.

Quantum computing is described as a process by which a system calculates output. Quantum physics usually refers to the smallest discrete unit of any property; the basic unit of data in quantum is the qubit; this qubit unit is equivalent to the bit unit in classical neural networks. Quantum deep learning combines quantum computing with deep learning to reduce training time for neural networks, which has proven effective in solving some intractable problems on classical computers. Quantum deep learning has proven effective in solving some intractable problems on classical computers. A quantum network can benefit from quantum information flow because it is a more efficient framework than classical systems. Each quantum deep learning consists of a quantum gate. In this review, we provide a comprehensive review of recent studies that include different quantum deep learning applications, including healthcare, handwriting, and many others. Also, methodologies, problems, main datasets, results, strengths, limitations, and challenges are included in this review. [ABSTRACT FROM AUTHOR]

In the field of image processing, a well-known model is the Convolutional Neural Network, or CNN. The unique benefit that sets this model apart is its exceptional ability to use the correlation information included in the data. Even with their amazing accomplishment, conventional CNNs could have trouble improving further in terms of generalization, accuracy, and computing economy. However, it could be challenging to train CNN correctly and process information quickly if the model or data dimensions are too large. This is since it will cause the data processing to lag. The Quantum Convolutional Neural Network, or QCNN for short, is a novel proposed quantum solution that might either enhance the functionality of an existing learning model or solve a problem requiring the combination of quantum computing with CNN. To highlight the flexibility and versatility of quantum circuits in improving feature extraction capabilities, this paper compares deep quantum circuit architecture designed for image-based tasks with classical Convolutional Neural Networks (CNNs) and a novel quantum circuit architecture. The covidx-cxr4 dataset was used to train quantum-CNN models, and their results were compared against those of other models. The results show that when paired with innovative feature extraction methods, the suggested deep Quantum Convolutional Neural Network (QCNN) outperformed the conventional CNN in terms of processing speed and recognition accuracy. Even though it required more processing time, QCNN outperformed CNN in terms of recognition accuracy. When training on the covidx-cxr4 dataset, this dominance becomes much more apparent, demonstrating how deeper quantum computing has the potential to completely transform image classification problems. [ABSTRACT FROM AUTHOR]

Giardia lamblia parasite was isolated from the diarrhea samples of patients with Giardiasis dysentery and was developed in HSP media, four mice groups have been used to find in vivo efficacy of two concentrations (128,256) mg/ml of chlorophorm extracts from Cladophora glomerata algae against Giardia lamblia parasite as compared with (Flagyl) by measuring several biochemical markers as ( GPT and GOT) enzymes ,sodium ,potassium and iron concentration as well as counting the number of parasitic cysts in each mice groups. The results demonstrate that levels of GPTA GOT enzymes have been decreased in mice treated with algal extract. As for the concentration of the Sodium, Potassium and Iron increased in mice treated with algal extract. The number of the Giardia cyst is also reduced in orally inoculated mice with both concentrations of algal extract as compared with positive control and the Flagyl treated group. In terms of bioactive compounds, GC-Mass results indicate the presence of many phytochemicals with different biologically active properties This study represents the first attempt to use Cladophora glomerata derived from phytochemicals to treat giardiasis in vivo.