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  1. Hasbi A, Shatriah I, A Rahim H, Zamli AH, Tai E
    Cureus, 2023 Dec;15(12):e50693.
    PMID: 38229775 DOI: 10.7759/cureus.50693
    This is a case of an orbital abscess evidenced radiologically in a 41-year-old female with no comorbidities. She was healthy and had no history of trauma or infection of the adjacent structures. She denied having symptoms of upper or lower respiratory and urinary tract infections. The decision for surgical drainage was made following a slow response to antimicrobial agents after 24 hours, a progressive painful erythematous eyelid swelling, and further deterioration of vision. Her clinical condition and visual acuity improved following cutaneous incision and drainage. Culture and sensitivity results for urine and orbital abscess were positive for Staphylococcus (S.) aureus. The patient regained full visual recovery without any sequelae. In conclusion, an orbital abscess is a blinding and life-threatening condition that rarely occurs in immunocompetent individuals and uncommonly arises from distant sources. A high index of suspicion, early institution of appropriate diagnostic imaging, and aggressive medical and surgical treatment are necessary for a favorable visual outcome in orbital abscess cases.
  2. Abdul Rani KN, Abdulmalek M, A Rahim H, Siew Chin N, Abd Wahab A
    Sci Rep, 2017 Apr 20;7:46521.
    PMID: 28425443 DOI: 10.1038/srep46521
    This research proposes the various versions of modified cuckoo search (MCS) metaheuristic algorithm deploying the strength Pareto evolutionary algorithm (SPEA) multiobjective (MO) optimization technique in rectangular array geometry synthesis. Precisely, the MCS algorithm is proposed by incorporating the Roulette wheel selection operator to choose the initial host nests (individuals) that give better results, adaptive inertia weight to control the positions exploration of the potential best host nests (solutions), and dynamic discovery rate to manage the fraction probability of finding the best host nests in 3-dimensional search space. In addition, the MCS algorithm is hybridized with the particle swarm optimization (PSO) and hill climbing (HC) stochastic techniques along with the standard strength Pareto evolutionary algorithm (SPEA) forming the MCSPSOSPEA and MCSHCSPEA, respectively. All the proposed MCS-based algorithms are examined to perform MO optimization on Zitzler-Deb-Thiele's (ZDT's) test functions. Pareto optimum trade-offs are done to generate a set of three non-dominated solutions, which are locations, excitation amplitudes, and excitation phases of array elements, respectively. Overall, simulations demonstrates that the proposed MCSPSOSPEA outperforms other compatible competitors, in gaining a high antenna directivity, small half-power beamwidth (HPBW), low average side lobe level (SLL) suppression, and/or significant predefined nulls mitigation, simultaneously.
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