Camera oscillation pattern for VSLAM: translational versus rotational

Visual SLAM algorithms exploit natural scene features to infer the camera motion and build a map of the environment landmarks. SLAM algorithm has two interrelated processes localization and mapping. For accurate localization, we need the features location estimates to converge quickly. On the other hand, to build an accurate map, we need accurate localization. Recently, a biologically inspired approach exploits deliberate camera oscillation has been used to improve the convergence speed of depth estimate. In this paper, we explore the effect of camera oscillation pattern on the accuracy of VSLAM. Two main oscillation patterns are used for distance estimation: translational and rotational. Experiments, using static and moving robot, are made to explore the effect of these oscillation patterns on the VSLAM performance

Dynamic feature detection using virtual correction and camera oscillations

Visual SLAM algorithms exploit natural scene features to infer the camera motion and build a map of a static environment. In this paper, we relax the severe assumption of a static scene to allow for the detection and deletion of dynamic points. A new "virtual correction" method is introduced which serves to detect the dynamic points by checking the re-projection error of the points before and after the virtual measurement update. It can also recover the erroneously excluded useful features, particularly the distant points which may be deleted because of the change in its position after new measurement observation. Deliberate camera oscillations are also used to improve the VSLAM accuracy and the camera observability. The simulation results showed the effectiveness of the virtual correction when combined with camera oscillation in recovering the misclassified features and detecting the dynamic features even in difficult scenarios

Evaluation of the Antibiotic Resistance Pattern at the Medical Services Administration Hospital in Khartoum, Sudan, 2021

The number of antibiotics available is limited and does not cover the growing antibiotic resistance challenge. Misuse and overuse of antibiotics act as factors that help in improving and increasing the problem of resistance to those currently being prescribed by doctors. The study was carried out at the Medical Services Administration Hospital (MSAH) in Khartoum, Sudan to investigate the antibiotic resistance pattern for the period between Dec. 2020 and Jan. 2022. The results showed that, in a total of different clinical samples that were collected and processed, a total number of 980 organisms were isolated. The result indicated that 345 out of the total isolates (35.20%) were Klebsiella pneumonia, 326 (33.27%) Escherichia coli, 154 (15.71%) Pseudomonas aeruginosa, 130 (13.27%) Proteus mirabilis, and 25 (2.55%) Staphylococcus aureus. The results showed that K. pneumonia was quite resistant to piperacillin, cefuroxime, and azithromycin. The amikacin, imipenem, and meropenem antibiotics showed significant activity against K. pneumonia. The isolates of E. coli showed significant resistance to azithromycin and were more sensitive to imipenem and meropenem. P. aeruginosa was resistant to penicillin, amoxicillin/clavulanic acid, and azithromycin in a big way, but it was very sensitive to cefuroxime, the drug used to treat strep throat infections. P. mirabilis was found to be resistant to nalidixic acid, nitrofurantoin, amoxicillin/clavulanic acid, and azithromycin. It showed good sensitivity to amikacin, imipenem, and meropenem. It was clear that S. aureus was resistant to cefuroxime, ceftriaxone, nitrofurantoin, and norfloxacin, while tests showed that it was sensitive to imipenem

Biofunctional molecules from Citrullus colocynthis: An HPLC/MS analysis in correlation to antimicrobial and anticancer activities

Background: Citrullus colocynthis belongs to Family Cucurbitaceae. It grows widely in Egypt and Sudan and it has been used in folk medicine of Sudan and many other African countries as anti inflammatory, anti diabetic, and antioxidant agent. Objectives: To evaluate the antibacterial, antifungal, antiviral, anticancer activities of ethanolic crude extracts of the fruits, leaves, seeds and roots of this plant, as well as identifying them HPLC/MS. Materials and Methods: Dried fruits, seeds, leaves and roots of C. colocynthis were powdered and passed through a 40- mesh, then, the powders were extracted with 95% ethanol in a soxhlet apparatus. The residues were dried under reduced pressure in rotary evaporator. Crude extract from different plant parts were evaluated biologically and phytochemically. Results: All extracts showed good antifungal activities with inhibition zone ranges between 15.1 ± 0.32 to 25.6 ± 0.16 mm. In terms of plant organ, fruits were the most active. In term of fungal strain Aspergillus fumigatus and Geotricum candidum were the most sensitive. Against tested Gram +ve, all extracts showed good activities except roots, while antibacterial activity against Gram –ve showed that the fruits extract have good activity as it was the sole extract with activity against Pseudomonas aeruginosa. Test for antiviral activities showed moderate to weak inhibitions of cytopathic effect (CPE). Anticancer activities of different crude extracts showed that fruits had significant antitumor activities against all tested cell lines, the IC50 values were 24.6, 16, 18.5 and 19.7 µg /ml for HCT-116, MCF-7, Hep-G2 and Caco-2 respectively. Seeds extract was only active on HCT-116 and Hep G2 with IC50 =21.2 µg/ml for HCT-116 and 22.4 µg/ml for Hep G2. Leaves extract was only active against Hep G2 cancer cell line with IC50 19.7 µg/ml. Roots extract show weak antitumor activity on tested cell lines (IC50 values > 30µg/ml). HPLC/MS qualitative and quantitative analysis of different organs extracts revealed the presence of 21 compounds identified as fourteen cucurbitacins, three flavonoids, three tannins, and one sterol. The presence of cucurbitacins can explain most of the biological activities. Conclusion: The biological activities of colocynth different parts are due to the presence of secondary metabolites mainly cucurbitacins in addition to flavonoids and tannins.  These activities prove the use of this plant in folk medicine and deserve much more future exploration targeting their discovery in unexplored sources and their derivatives for improving their anticancer and antimicrobial abilities. Keywords: Citrullus colocynthis, crude extracts, antifungal, antibacterial, antiviral, anticancer, HPLC/M

Green nanotechnology: Anticancer Activity of Silver Nanoparticles using Citrullus colocynthis aqueous extracts

Green synthesis of metal nanoparticles is a growing research area because of their potential applications in nanomedicines. The green synthesis of silver nanoparticles (SNPs) is a convenient, cheap and environmentally safe approach compared to chemical synthesis. In the present study, we synthesized SNPs from AgNO3 using aqueous extracts (AEs) of fruits, leaves, roots and seeds of Citrullus colocynthis as reducing and capping agents. The SNPs were early detected in the aqueous extracts by color change to the reddish brown, and further were confirmed by Transmission Electron Microscope (TEM) analysis. The TEM analysis of SNPs showed spherical nanoparticles with mean size between 7 to 19nm. The anticancer activity of SNPs has been assessed invitro.  MTT assay on human cancer cell lines of colon (HCT-116), breast (MCF-7), liver (Hep-G2) and intestine (Caco-2) showed good anticancer activity which was negligible for the aqueous plant extracts. Regarding to the tested cell lines the Hep-G2 cell line and HCT-116 were the most sensitive cell line towards the cytotoxic activities of the tested SNPs, while the Caco-2 was the most resistant cell line towards the cytotoxic activities. Keywords: green synthesis, silver nanoparticles, Citrullus colocynthis, anticancer

Fighting the Progress of COVID-19 by Enhancing Immunity: A Review of Traditional Sudanese Natural Products Containing Immune-Boosting Elements

The World Health Organization has classified the coronavirus disease outbreak as a worldwide pandemic as a result of the COVID-19 expansion. According to medical professionals, individuals with strong immunity often outlive infections more frequently than those with poor immunity. The COVID-19 pandemic has prompted the need for novel approaches to treating the illness and its symptoms. Natural products from plants are increasingly being seen favorably in comparison to synthetic ones in the fight against diseases. As a result, in order to avoid contracting any unanticipated illnesses, individuals must increase their immunity by eating more dietary supplements and by taking drugs that have immune-boosting properties. This review aimed to give a general overview of some traditional Sudanese foods and drinks that are rich in immune-boosting elements, and accordingly, they could be safely recommended as an adjuvant dietary supplement to improve the immune system\u27s ability to fight such infections as COVID-19. Also, this review aims to bring attention to the fact that immune boosters may be found in natural sources, which will help pharmaceutical companies by taking some of the load off of them. Electronic databases, including Google Scholar, Scopus, and the Web of Science, were searched for relevant material. The selected articles underwent independent eligibility and information extraction reviews. The review focused on certain traditional Sudanese herbs and their derivatives that are rich in immune-stimulating vitamins and minerals and therefore could possibly be recommended as immune-boosting dietary supplements to help fight COVID-19. This review highlights the fact that the pharmaceutical sector, especially community and hospital pharmacists, could play a vital role in supporting the healthcare system by encouraging their communities to add plants and their products that are rich in immune-boosting vitamins and minerals to their diet

A Deep Learning Approach for Vital Signs Compression and Energy Efficient Delivery in mhealth Systems

© 2013 IEEE. Due to the increasing number of chronic disease patients, continuous health monitoring has become the top priority for health-care providers and has posed a major stimulus for the development of scalable and energy efficient mobile health systems. Collected data in such systems are highly critical and can be affected by wireless network conditions, which in return, motivates the need for a preprocessing stage that optimizes data delivery in an adaptive manner with respect to network dynamics. We present in this paper adaptive single and multiple modality data compression schemes based on deep learning approach, which consider acquired data characteristics and network dynamics for providing energy efficient data delivery. Results indicate that: 1) the proposed adaptive single modality compression scheme outperforms conventional compression methods by 13.24% and 43.75% reductions in distortion and processing time, respectively; 2) the proposed adaptive multiple modality compression further decreases the distortion by 3.71% and 72.37% when compared with the proposed single modality scheme and conventional methods through leveraging inter-modality correlations; and 3) adaptive multiple modality compression demonstrates its efficiency in terms of energy consumption, computational complexity, and responding to different network states. Hence, our approach is suitable for mobile health applications (mHealth), where the smart preprocessing of vital signs can enhance energy consumption, reduce storage, and cut down transmission delays to the mHealth cloud.This work was supported by NPRP through the Qatar National Research Fund (a member of the Qatar Foundation) under Grant 7-684-1-127

Mechatronics Design of an Autonomous Pipe-Inspection Robot

Pipelines require periodical inspection to detect corrosion, deformation and congestion with obstacles in the network. Autonomous mobile robots are good solutions for this task. Visual information from the pipe interior associated with a location stamp is needed for inspection. In this paper, the previous designs of autonomous robots are reviewed and a new robot is developed to ensure simple design and smooth motion. Images are processed online to detect irregularity in pipe and then start capturing high resolution pictures to conserve the limited memory size. The new robot moves in pipes and provides video stream of pipe interior with location stamp. The visual information can later be processed offline to extract more information of pipeline condition to make maintenance decisions

Mild Cognitive Impairment among Type II Diabetes Mellitus Patients Attending University Teaching Hospital

BACKGROUND: Type II diabetes mellitus (TIIDM) has been associated with structural and functional changes in the brain. TIIDM is commonly associated with obesity, insulin resistance, hypertension, and dyslipidemia, all of which can have negative impact on brain. AIM: The aim of the study was to study the risk of mild cognitive impairment (MCI) among both diabetics and non-diabetics and to identify risk factors to MCI among both groups. METHODS: Two comparative cross-sectional studies were carried out enrolling 100 diabetics and 100 age, sex, and education matching non-diabetics. Cognitive function was assessed using Montreal Cognitive Assessment (MoCA) test and risk factors for MCI were assessed. RESULTS: The subjective complaint of memory impairment among diabetics was significantly higher (34%) compared to non-diabetics (13.0%), p < 0.05. The mean of objective MoCA score was significantly lower among diabetics (25.9 ± 2.5) compared to non-diabetics (27.4 ± 2.4), p < 0.001. The rate of MCI was significantly higher among TIIDM patients (22%) compared to non-diabetics (9%), p < 0.01 and odds ratio (OR) 2.8 (95% confidence interval 1.2–6.5). Among the two studied groups, the rate of MCI was significantly higher among those aged over 50 years compared to younger age as well as among hypertensive compared to non-hypertensive persons, (p < 0.05). Among diabetics, the MCI was significantly higher among those with secondary education, having heart diseases, longer duration of DM, or repeated hypoglycemia attack, p < 0.05. A healthy diet, brain training, and social activities were found to be significantly associated with normal cognition. Logistic analysis revealed that diabetics aged above 50 was the only significant predicting factor for MCI with an OR 2.9 (95% CI: 3.8–123.3), p < 0.001. CONCLUSION: TIIDM is significantly associated with 3-times increasing risk of having MCI compared to non-diabetics. The age, hypertension, cardiovascular diseases, duration of diabetes, and frequency of hypoglycemic episodes are risk factors for cognitive impairment. A healthy diet, brain training, and social activities were associated with better cognitive function

Changing Survival Rate of Infants Born Before 26 Gestational Weeks : Single-centre study

 Objectives: This study aimed to evaluate the changing survival rate and morbidities among infants born before 26 gestational weeks at the Sultan Qaboos University Hospital (SQUH) in Muscat, Oman. Methods: This retrospective study assessed the mortality and morbidities of all premature infants born alive at 23–26 gestational weeks at SQUH between June 2006 and May 2013. Infants referred to SQUH within 72 hours of birth during this period were also included. Electronic records were reviewed for gestational age, gender, birth weight, maternal age, mode and place of delivery, antenatal steroid administration, morbidity and outcome. The survival rate was calculated and findings were then compared with those of a previous study conducted in the same hospital from 1991 to 1998. Rates of major morbidities were also calculated. Results: A total of 81 infants between 23–26 gestational weeks were admitted to the neonatal unit during the study period. Of these, 58.0% were male and 42.0% were female. Median gestational age was 25 weeks and mean birth weight was 770 ± 150 g. Of the 81 infants, 49 survived. The overall survival rate was 60.5% compared to 41% reported in the previous study. Respiratory distress syndrome (100.0%), retinopathy of prematurity (51.9%), bronchopulmonary dysplasia (34.6%), intraventricular haemorrhage (30.9%) and patent ductus arteriosus (28.4%) were the most common morbidities. Conclusion: The overall survival rate of infants between 23–26 gestational weeks during the study period had significantly improved in comparison to that found at the same hospital from 1991 to 1998. There is a need for the long-term neurodevelopmental follow-up of premature infants