Investment in SARS-CoV-2 sequencing in Africa over the past year has led to a major increase in the number of sequences generated, now exceeding 100,000 genomes, used to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence domestically, and highlight that local sequencing enables faster turnaround time and more regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and shed light on the distinct dispersal dynamics of Variants of Concern, particularly Alpha, Beta, Delta, and Omicron, on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve, while the continent faces many emerging and re-emerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century.
Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breathing difficulty) used to diagnose the person being infected by COVID-19 virus or not. Secondly, this approach divides the infected peoples into four classes, based on their immune system risk level (very high degree, high degree, mild degree, and normal), and using two indices of age and current health status like diabetes, heart disorders, or hypertension. Where, these people are graded and expected to comply with their class regulations. There are six important COVID-19 virus infections of different classes that should receive immediate health care to save their lives. When the test is positive, the patient age is considered to choose one of the six classifications depending on the patient symptoms to provide him the suitable care as one of the four types of suggested treatment protocol of COVID-19 virus infection in COVID-19 DSS application. Finally, a report of all information about any classification case of COVID-19 infection is printed where this report includes the status of patient (infection level) and the prevention protocol. Later, the program sends the report to the control centre (medical expert) containing the information. In this paper, it was suggested the use of C4.5 Algorithm for decision tree.
In this paper, the Power system stabilizer (PSS) and (PID) are enhanced with a Chaotic Particle Swarm Optimization (CPSO) Damping Controller in order to suppression the Low-Frequency Oscillations (LFO) in a Single Machine Infinite Bus (SMIB) power system. Chaotic particle swarm optimization (CPSO) is used to tune the parameters of the PSS-PID. The design damping controller is an optimized lead-lag controller, which extracts the speed deviation of the generator rotor and generates the output feedback signal, which aims to modulate the reference values of the PSS-PID controller to achieve the best damping of LFO. In order to search the better damping option, the damping controller is applied to a series of the PSS-PID and the results are compared in two cases (PSS without PID and PSS with PID). The effectiveness of the proposed controller is achieved by time-domain simulation results in MATLAB environment, using three different operational conditions (Nominal, Light, and heavy). In addition, the results obtained from the PSS-PID were robust and more efficient compared to the PID only in terms of oscillations damping, overshoot minimizing and settling time reducing.
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