Spread enhancement for firefly algorithm with application to control mechanism of exoskeleton system

Firefly algorithm (FA) is a swarm intelligence based algorithm for global optimization and has widely been used in solving problems in many areas. The FA is good at exploring the search space and locating the global optimum, but it always gets trapped at local optimum especially in case of high dimensional problems. In order to overcome such drawbacks of FA, this paper proposes a modified variant of FA, referred to as spread enhancement strategy for firefly algorithm (SE-FA), by devising a nonlinear adaptive spread mechanism for the control parameters of the algorithm. The performance of the proposed algorithm is compared with the original FA and one variant of FA on six benchmark functions. Experimental and statistical results of the approach show better solutions in terms of reliability and convergence speed than the original FA especially in the case of high-dimensional problems. The algorithms are further tested with control of dynamic systems. The systems considered comprise assistive exoskeletons mechanism for upper and lower extremities. The performance results are evaluated in comparison to the original firefly and invasive weed algorithms. It is demonstrated that the proposed approaches are superior over the individual algorithms in terms of efficiency, convergence speed and quality of the optimal solution achieved

Power system design using firefly algorithm for dynamic stability enhancement

Utilising additional devices in power systems have been developed by industry. Devices such as a Power System Stabilizer (PSS) and a Superconducting Magnetic Energy Storage (SMES) are commonly employed in industry. This work investigated the coordination of a PSS and SMES applied to a power system to enhance dynamic stability. To obtain optimal coordination, the parameters of the PSS and SMES are tuned using the Firefly Algorithm (FA). The simulation of the power system, PSS, and SMES has been performed using MATLAB and Simulink, and the FA run in Matlab. For testing the small signal stability, the eigenvalue of the system will be investigated, while for dynamic stability the system will be given an external disturbance. The rotor angle and frequency deviation of the power system are compared without a controller, with a PSS and SMES included, and with the PSS and SMES tuned by FA. The simulation results show that the proposed system can improve not only small signal stability (steady state stability) but also dynamic stability

Statistical and nature-inspired metaheuristics analysis on flexirubin production

Nowadays, demand for natural pigments has increased dramatically due to the awareness of the toxicity of some synthetic pigments. Because of the high cost of growth medium for natural pigment production, various studies have been carried out to explore medium which are less costly, such as agricultural waste. This study highlight on the application of firefly algorithm (FA) and bat algorithm (BA) in optimizing yellowish-orange pigment production (flexirubin) from the agricultural waste material. At present, response surface methodology (RSM) is the most preferred statistical method in optimizing pigment production. However, in the last two decades, nature-inspired metaheuristics approach has been used extensively in the fermentation process and have continually improve the efficiency in the optimization problem especially in pigment production. This study compared the analytics studies of RSM, FA and BA in the estimation of fermentation parameters (Lactose, Ltryptophan, and KH2PO4) in flexirubin production from Chryseobacterium artocarpi CECT8497T. All models provided similar quality predictions for the above three independent variables in term of flexirubin production with bat algorithm showing more accurate in estimation, with the coefficient value of 98.87% compare to RSM 98.20% and FA 98.38%

Drug development progress in duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is a severe, progressive, and incurable X-linked disorder caused by mutations in the dystrophin gene. Patients with DMD have an absence of functional dystrophin protein, which results in chronic damage of muscle fibers during contraction, thus leading to deterioration of muscle quality and loss of muscle mass over time. Although there is currently no cure for DMD, improvements in treatment care and management could delay disease progression and improve quality of life, thereby prolonging life expectancy for these patients. Furthermore, active research efforts are ongoing to develop therapeutic strategies that target dystrophin deficiency, such as gene replacement therapies, exon skipping, and readthrough therapy, as well as strategies that target secondary pathology of DMD, such as novel anti-inflammatory compounds, myostatin inhibitors, and cardioprotective compounds. Furthermore, longitudinal modeling approaches have been used to characterize the progression of MRI and functional endpoints for predictive purposes to inform Go/No Go decisions in drug development. This review showcases approved drugs or drug candidates along their development paths and also provides information on primary endpoints and enrollment size of Ph2/3 and Ph3 trials in the DMD space