The Future Importance of Travel Health in the Middle East: Oman’s opportunity to enhance its services

EDITORIA

Stable Isotope Composition of Cyclone Mekunu Rainfall, Southern Oman

Cyclone Mekunu hit the southern Arabian Peninsula in late May 2018 and brought rainfall amounts that accounted for up to 6 times the mean annual precipitation. Coming from the Arabian Sea, a quite underdocumented region with regard to cyclones, the storm eye crossed the Omani coast approximately 80 km east of the border to Yemen. Using automatic samplers, rainfall samples were collected during the event at three locations along a transect almost parallel to the storm track. The stable isotope analyses show a wide range of δ values, with minimum and maximum values of −17.01‰ δ18O and −1.77‰ δ18O and −122.2‰ δ2H and −1.6‰ δ2H. On average, rainfall becomes isotopically lighter with elevation, but rather irregularly. In view of high wind speeds probably precluding a gradual rainout of ascending air masses, a “pseudo elevation effect” seems likely. Our measurements expand the known δ value range of local cyclones by about 6‰ for δ18O and by nearly 50‰ for δ2H. The isotopic composition of the annual Indian Summer Monsoon shows values of −0.93‰ δ18O to 2.21‰ δ18O and −2.1‰ δ2H to 23.7‰ δ2H. Thus, there is a clear difference in the dual isotope signatures of the two precipitation systems in the area. Our findings enable an assessment of the impact of cyclones on the hydro(geo)logical system. For the arid Najd area, we demonstrate that the isotopic signatures of groundwater samples fall between those of cyclone and (paleo)monsoon precipitation, suggesting that several rainfall types may have contributed to replenishment

Leaving Against Medical Advice Among Patients With Brain Tumours in the Middle East: Khoula Hospital Experience

Background: Leaving against medical advice (LAMA) can be defined broadly as a patient’s insistence upon leaving the hospital against the treating team has expressed advice, which is both a challenge and concern for physicians, as these patients lost to follow-up, and their outcomes remain unknown. There is no previous study conducted to find the prevalence and causes of LAMA in brain tumors patients in the Middle East to the best of our knowledge.Methods: Patients studied in this research are those who were diagnosed with any type of brain tumors and were admitted to the Neurosurgical Department in Khoula Hospital (KH) but signed LAMA in the two years between January 2017 to December 2018 by going through the electronic medical records. Data obtained from the health information system includes socioeconomic characteristics, health status-related data, diagnosis-related data, and the reasons for LAMA.Results: A total number of 302 patients with brain tumors included in this study. Twenty-eight patients (9.2%) signed LAMA with a majority of those who signed LAMA were in the young adult’s group (3-39 years) and represented 18 (64%). Eight patients (28.57%) among the LAMA group and 43 patients (15.69%) in the non-LAMA group have tumors in the frontal lobe, which has found to be the most familiar location (29%). There was a significant relationship between the reason for LAMA and gender (P = 0.020).Conclusion: Younger patients, male, Omani, newly diagnosed tumors, and tumors in the frontal lobe were all risk factors for LAMA. Education and awareness about LAMA recommended in order to avoid readmission and loss of follow up

Clinical and Autoimmune Profiles of Omani Patients with True Versus False Positive Autoimmune Encephalitis Antibodies Panels

The incidence of autoimmune encephalitis (AE) is rising due to increased awareness of the condition and detection of new autoantibodies. Coinciding with this rise are false positive autoantibodies without clinical correlates. Objective: To explore the clinical profiles of Omani patients who are truly positive for AE autoantibodies and compare them with those with false-positive autoantibodies. Methods: We reviewed the medical records of all patients who tested positive for AE antibody from May 2016 to December 2022. Cases were verified by three neurologists based on the existing criteria for AE. Results: The participants comprised N = 67 patients, 19 (28%) of whom fulfilled the criteria for AE. True-positive AE patients were younger with mean age of 35.3 ± 4.7 years (p = 0.010). They were also more likely to present with subacute memory disturbances (6/19; 32%; p = 0.030), seizures (12; 63%; p = 0.028), abnormal electroencephalogram (EEG) findings (10; 65%; p = 0.040), and abnormal signals in limbic region on magnetic resonance imaging (MRI) (5; 26%; p = 0.010). Subacute memory disturbance was a significant predictor for true positivity (OR = 17.807, 95%CI = 1.608–197.202; p = 0.019). Anti-N-methyl-d-aspartate receptor (NMDAR) encephalitis was the most frequent type of AE (8; 42.1%), followed by anti-glutamic acid decarboxylase 65 (GAD65) (4; 21.1%). Conclusion: Of the 67 cases with positive AE autoantibody panel, 48 (72%) were false-positive. The presence of subacute memory impairment was a significant predictor of AE. Anti-NMDAR encephalitis was the most frequent AE encountered in our cohort

Autonomous Coverage Expansion Of Mobile Agents Via Cooperative Control And Cooperative Communication

In this paper, a distributed extremum seeking and cooperative control is designed for mobile agents to disperse themselves optimally in maintaining communication quality and maximizing their coverage. The agents locally form a virtual MIMO communication system, and they communicate among them by using the decode and forward cooperative communication. Outage probability is used as a measure of communication quality which can be estimated real-time. A general performance index balancing outage probability and spatial dispersion is chosen for the overall system. Extremum seeking control approach is used to estimate the optimal values specified by the performance index, and cooperative formation control is applied to move the agents to the optimal locations by using only the locally-available information. The network connectivity and coverage are much improved when compared to either non-cooperative communication approaches or other existing control results. Simulation analysis is carried out to demonstrate the performance and robustness of the proposal methodology, and simulation is done to illustrate its effectiveness. © 2014 Springer-Verlag

Professional development needs among school principals in the context of educational reform in Muscat, Oman / Saleh Said Hamad Al-Abri

The purpose of this study was to identify the core professional development needs of school principals in Muscat in the context of educational reform in Oman since 1998, when the general education curriculum was revamped to the basic education curriculum. The core professional development needs were initially identified and categorized into fifteen main areas and could be typified into two general types, that is, those concerning instructional matters (instructional leadership) and innovative initiatives (transformational leadership). This study also investigated challenges faced by school principals and their suggestions for improving school leadership and management in Muscat, Oman. The study largely used the survey method, which involved 80 school principals in the capital city of Muscat. As many as 25 principals from Cycle 1 and 55 principals from Cycle 2 participated in the study and they fully responded to the professional development needs survey questionnaire. Apart from the survey method, school visitations were made and some principals were interviewed to elicit information through face-to-face interactions regarding challenges, problems, and improvement efforts in school leadership and management related to school reform. Data obtained by survey was analyzed by descriptive statistics and inferential statistics using the SPSS software version 16. Descriptive statistics was used to assess principals’ perceptions regarding the extent of their professional development needs. Apart from that factorial analysis was used to examine the tenability of item groupings into their relevant factors, and to determine the dominant factors for professional development. Correlation matrix was also constructed to determine the inter-factor relational coherency. The results of the study showed that there were essentially fifteen areas or factors needed for professional development of school principals in the reform context. A majority of factors pertained to instructional matters, while other factors were concerned with leadership initiatives in making relevant changes suitable for new education policies and curriculum. Among the factors, building community involvement, leadership capacity, and problem solving were the dominant factors. Most principals contended that many professional development programs organized by the Ministry of Education did not match their professional development needs and roles. School principals were not properly trained in many aspects of school management and leadership. The implications of this study are: total retraining of school principals is needed whenever a system reform takes place, and new leadership competencies are needed to implement new policies and changes

A multi-layer swarm control model for information propagation and multi-tasking

Modeling and control of multi-agent systems is an important problem due to its large variety of potential applications and increasing practical and theoretical challenges. A large part of inspiration for modeling and control of multi-agent systems originates from the study of natural collective behaviors observed for example in schools of fish, flocks of birds, colonies of ants and cultures of bacteria. While individuals in these natural swarms are collectively performing complex tasks such as foraging or synchronization, critical information such as predator warnings propagate across the swarm almost instantly and presumably without explicit communication between the individuals. On the other hand, algorithms for multi-agent systems to locate a source or to follow a desired level curve of spatially distributed scalar fields generally require sharing field measurements among the agents for gradient estimation. The dependence on the exchange of data through a communication channel is a hard requirement that might be undesired especially in applications with severe limitations such as underwater robotics. The main contribution of this Dissertation is a Multi-Layer control model composed of an interplay of decentralized algorithms for perception and swarming. In the perception layer, each agent applies a Principal Component Analysis (PCA) on the relative positions and headings of its neighbors to learn principal properties about the motion and the geometry of the spatial distribution of the surrounding agents. These principal components are then used in the swarming layer where various distributed control laws are designed to balance between achieving a collective task and at the same time allowing critical emerging signals to propagate to the entire swarm. Within this Multi-Layer model, we contributed distributed control laws for swarms to perform collective source seeking and level curve tracking of scalar fields. These control laws scale to swarms of various sizes and graph structures and do not rely on explicitly estimating the field gradient or explicitly sharing measurements among the agents. Additionally, we contributed a distributed control law that balances between achieving a collective task and at the same time allowing critical signals to propagate to the entire swarm. Through this, we demonstrated implicit information propagation in swarms exhibiting predator-avoidance behavior using only local interactions and without explicit communication or prescribed formations. Moreover, we obtained various stability results reflecting the convergence and robustness of the proposed algorithms. Finally, we validated the proposed model for source seeking, level curve tracking and predator avoidance behaviors through various simulation and experimental results. The proposed control model offers a new method that enables robots with limited resources to perform diverse swarming activities with only local information. Additionally, designing analytical models to understand information propagation will not only reveal natural mysteries but additionally will help to propose multi-tasking control algorithms for robotic swarms that require only very limited or no explicit communication.Ph.D

Distributed field mapping for mobile sensor teams using a derivative‐free optimisation algorithm

Abstract The authors propose a distributed field mapping algorithm that drives a team of robots to explore and learn an unknown scalar field using a Gaussian Process (GP). The authors’ strategy arises by balancing exploration objectives between areas of high error and high variance. As computing high error regions is impossible since the scalar field is unknown, a bio‐inspired approach known as Speeding‐Up and Slowing‐Down is leveraged to track the gradient of the GP error. This approach achieves global field‐learning convergence and is shown to be resistant to poor hyperparameter tuning of the GP. This approach is validated in simulations and experiments using 2D wheeled robots and 2D flying miniature autonomous blimps