Search

Power flow, planning, economics, dispatch, and stability analysis rely on accurate transmission line parameters (TLPE). Standard optimization methods are employed to develop such analyses and obtain TLPE. Additionally, these methods have limitations, including precision, accuracy, and time complexity. It is challenging to find improved solutions using standard optimization methods due to slow convergence and limitations in identifying local optima. Concerned with these challenges, the study suggest a new application for an effective hybrid optimization method capable of addressing such limitations. The hybrid algorithm, named the Salp Swarm Algorithm with Sine Cosine Algorithm (HSSASCA), that aims to tackle the issues of slow convergence and local optima. The Sine Cosine Algorithm (SCA) is employed after the Salp Swarm Algorithm (SSA), and Salp integration is utilized to successfully explore and analyze the search space. To enhance the performance of HSSASCA, the hybrid technique aims to provide expanded exploration capabilities, effective exploitation of the search space, and a better convergence rate. These key features position the HSSASCA algorithm as an effective solution to complex optimization problems. To assess the efficiency of the HSSASCA algorithm, six different test systems are employed. Initially, the evaluation of exploration, exploitation, and minimized local optima is conducted using the CEC 2019 benchmark functions. Secondly, efficiency monitoring and verification of HSSASCA across different scenarios occur by comparing it with established optimization algorithms such as SSA, SCA, firefly optimization algorithm (FFO), Grey Wolf Optimization (GWO), student psychology‐based optimization (SPBO), and Symbiotic Organisms Search (SOS). Finally, statistical analysis is performed, revealing that the HSSASCA outperforms SSA, SCA, FFO, GWO, SPBO, and SOS. In terms of statistical results and convergence curves, the HSSASCA demonstrates superior performance in searching efficiency, convergence accuracy, and local optimum avoidance ability. [ABSTRACT FROM AUTHOR]

Background: Toxic Epidermal Necrolysis (TEN), also known as Lyell's syndrome, is a rare but severe connective tissue condition that is a common cause of substantial skin damage as well as mucous membrane breakdown. This condition is distinguished by the detachment of the epidermis presenting as blisters and denuded skin areas along with erythema. Supportive care is typically the mainstay in the primary treatment of TEN. The effectiveness of systemic steroids remains uncertain due to the limited availability of studies that directly compare the utility of these therapeutic approaches. Here, we report a case where TEN was successfully treated with dexamethasone. Case Presentation: We present a case of an 18-year-old female patient who presented with complaints of itchy skin lesions, multiple purpuras and petechiae following ingestion of a dose of a cefadroxil tablet. A diagnosis of cefadroxil-induced Toxic Epidermal Necrolysis was made. Hydration therapy along with systemic steroids and topical treatments were administered to the patient. The lesions healed gradually and the condition of the patient improved. [ABSTRACT FROM AUTHOR]

COVID-19 primarily impacts the respiratory system, with neurological manifestations often being thrombotic and affecting the nervous system. However, the specific presentation of demyelinating manifestations remains less clearly defined. While recent research has established a connection between COVID-19 and Guillain-Barré syndrome-a complex neurological disorder characterised by acute or chronic degeneration-the extent of this association and the distinctive features of GBS within this context remain uncertain. In this report, we present the case of acute GBS suspected to be induced by a COVID-19 infection. Notably, this patient did not exhibit any preceding respiratory, gastrointestinal, or systemic illnesses. Consequently, this case underlines the critical importance of acknowledging the potential risk of Guillain-Barré Syndrome following a COVID-19 infection, making a significant contribution to raising awareness about this potential association. [ABSTRACT FROM AUTHOR]

This paper proposes a novel hybrid algorithm which is mathematically modelled by amalgamating the superior features of recently developed Grey Wolf Optimizer (GWO), Sine Cosine Algorithm (SCA), and Crow Search Algorithm (CSA). Researchers have already implemented the aforementioned three algorithms and obtained superior quality results for solving diverse optimization problems. The novel hybrid Variegated GWO Algorithm (VGWO) developed in this proposed research work is initially realized and validated for solving IEEE CEC-C06 2019 benchmark functions. Thereafter, the proposed VGWO is utilized as an optimization tool to solve three emerging and complex power system optimization problems which includes energy management of microgrid systems operated in both islanded and grid-connected mode, dynamic economic emission dispatch and reactive power planning (RPP) problem. A comparative analysis of the proposed VGWO approach with other established metaheuristics is undertaken for each optimization problem. Numerical results show that the novel hybrid VGWO algorithm outperformed an ample number of optimization techniques in providing better quality solutions. The proposed hybrid algorithm yielded a 36.93% reduction in active power loss and 36.80% reduction in operating cost with respect to base case condition for RPP problem. Likewise while solving microgrid energy management problems 9–30% savings was realized in the generation cost compared to the ones mentioned in literature. The capability of handling many complex constraints within a minimum amount of computational time to provide consistently best solutions prioritize the proposed hybrid algorithm among its kinds. Statistical analysis validates the authenticity and viability of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Globally, mountain systems are unevenly exposed to risks of extreme precipitation. Within the Himalayan region, precipitation extremes are a rising concern, but their current understanding is limited. In this study, we use 113 years of precipitation data to rank and characterize precipitation extremes in the Indian Western Himalayas (IWH). Our statistical ranking method integrates precipitation spatial extent and its intensity across different durations for determining the severity of extreme events. The proposed ranking method accounts for multi‐day duration ranking method to capture persistent precipitation episodes. Results show that the method accurately detects and ranks the most extreme precipitation events that occurred in the IWH and indicate locations of these events. Our results highlight that critical long duration events in the region (e.g., 10 days) are missed at ranks at shorter duration (e.g., 2–3 days), thereby highlighting the importance to multi‐day precipitation extremes ranking. In addition, the proposed ranking method provides information about the event duration that will be associated with the highest impact on society, carrying high significance. Our findings are valuable for flood risk management and disaster risk reduction. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The degradation of ampicillin via solar photo-Fenton oxidation was investigated. • Ampicillin degradation rate constant was raised with increasing the solution’s pH. • Complete inactivation of total cultivable and AMP-resistant E. coli was observed. • No regrowth of E. coli was observed after 24 and 48 h of incubation at 37 °C. • Complete elimination of effluents’ toxicity was achieved after 180 min of treatment. Abstract Urban, hospital and pharmaceutical industry wastewater effluents are among the main sources of antibiotics’ and other antimicrobial agents’ contamination in soil and water ecosystems, especially in countries where wastewater reuse is applied. Ampicillin (AMP), which is the first semi-synthetic broad spectrum penicillin that was released on the market in 1961 has been detected in treated wastewater effluents worldwide, at concentrations ranging from sub-ng/L up to 27 μg/L, as well as in various environmental aqueous matrices up to 13.7 μg/L, highlighting its recalcitrance to conventional biological treatment. Nevertheless, the degradation potential of AMP via advanced chemical oxidation processes, which are widely considered as promising alternatives of conventional technologies, hardly has been investigated. Thus, this study aims at assessing the efficiency of solar photo-Fenton process at degrading AMP from secondary-treated wastewater effluents under various experimental conditions. The degradation rate of AMP via solar photo-Fenton oxidation fitted well the pseudo-first-order kinetic model. AMP was completely degraded after 30 min of treatment at various H 2 O 2 doses (25–100 mg/L) under acidic pH, while its degradation was pronounced at mild alkaline conditions (inherent pH) (100% removal after 5 min). Total cultivable and AMP-resistant E. coli was completely inactivated after 180 min of treatment at the optimum operational conditions, and no regrowth was observed. Finally, the ecotoxicity results showed that the process was capable of eliminating the toxicity towards Daphnia magna after 180 min, providing thus a more complete evaluation of the overall efficiency of the process. [ABSTRACT FROM AUTHOR]

Summary: This article proposes a new meta‐heuristic optimization algorithm named grey wolf optimization algorithm based on leadership and hunting behavior of grey wolf for the reactive power planning of a connected power network. The performance of the proposed opposition‐based grey wolf optimization (OGWO) and grey wolf optimization (GWO) is examined and tested successfully in standard IEEE 14, IEEE 30, and IEEE 57 bus test systems for the minimization of active power loss and the total operating cost while maintaining voltage profile of the buses within permissible limit. Active power loss and total operating cost are minimized by optimal planning of the reactive generation of generators, transformer tap setting arrangements, and reactive output of shunt capacitors as installed at weak nodes under different loading conditions. The weak nodes are detected by power flow analysis. The results obtained by GWO algorithm is compared to other popular techniques recently reported in recent state‐of‐the‐art literature. It is observed that proposed OGWO and GWO algorithm yields much better result in terms of reducing operating cost and minimizing active power loss. Merit lies with GWO is that its simple structure for implementation and its ability not to be trapped in local minima, thus exploring wider search area. [ABSTRACT FROM AUTHOR]

In the present work, reactive power planning problem along with voltage stability margin is addressed by effective co-ordination of reactive power sources. Modal analysis and L-index methods are used to detect weak nodes of the system accordingly. Differential Evolution (DE) and Genetic Algorithm (GA)-based optimization techniques are applied for the proper co-ordination of Var sources under base and increased loading conditions maintaining voltage stability of the connected power network. The problem is multi-objective and IEEE 30 bus system is taken as the standard system. It is observed that modal analysis based detection of weak nodes are more effective than the L-index-based detection. Moreover, the DE-based optimization algorithm gives better result compared to GA-based approach in maximizing reactive power reserves. [ABSTRACT FROM AUTHOR]

In the proposed work, authors have applied swarm intelligence based algorithms for the effective Co-ordination of Flexible AC transmission system (FACTS) devices with other existing Var sources present in the network. IEEE 30 and IEEE 57 bus systems are taken as standard test systems. SPSO (Simple Particle Swarm Optimization) and other two swarm based intelligence approaches like APSO (Adaptive Particle Swarm Optimization) and EPSO (Evolutionary Particle Swarm Optimization) are used for the optimal setting of the Var sources and FACTS devices. The result obtained with the proposed approach is compared with the result found by the conventional RPP (Reactive power planning) approach where shunt capacitors, transformer tap setting arrangements and reactive generations of generators are used as planning variables. It is observed that reactive power planning with FACTS devices yields much better result in terms of reducing active power loss and total operating cost of the system even considering the investment costs of FACTS devices. [ABSTRACT FROM AUTHOR]

Reactive power source planning problem has significant role for secure and economic operation of power system. Reactive power planning problem is nothing but the proper coordination of existing Var sources which lead to loss minimization and cost economic operation of the system. In the proposed approach several bio-inspired algorithms like Particle Swarm Optimization (PSO), Evolutionary Particle Swarm Optimization (EPSO), Adaptive Particle Swarm Optimization (APSO), Hybrid Particle Swarm Optimization (HPSO) and Bacterial Foraging Algorithm (BFA) are used for the reactive power planning problem. Finally a comparison of all these techniques are made on the basis of the results obtained when applied to different standard test system. [ABSTRACT FROM AUTHOR]

• Different electricity market pricing strategies were studied. • Generation cost was minimized for all the strategies on 2 MG test systems. • Novel hybrid GWOSCACSA was proposed as optimization tool. • Proposed GWOSCACSA was realized on 15 benchmark functions. • Comparative analysis among strategies was done. • Statistical analysis was performed on results obtained. The upsurge in microgrid demand is an important aspect of imparting energy in future primarily because of the involvement of renewable energy sources, which alleviates the emission of toxic gases from fossil fuelled generators. The grid-connected mode of microgrid operation is the most economical and definitive mode of service wherein the grid is actively involved in the buying and selling of power prompting diminished generation cost of microgrid system. These cases, pertaining to two different low voltage microgrid systems, are applied consecutively for obtaining the generation cost of the systems and thus devise the cheapest strategy among them. The Grey Wolf Optimizer (GWO) is improvised by incorporating strategies from population-based Sine Cosine Algorithm (SCA) along with position updating methods of crows from Crow Search Algorithm (CSA) to form a hybrid modified Grey Wolf Optimizer Sine Cosine Algorithm Crow Search Algorithm (GWOSCACSA) algorithm. The implementation of the proposed technique produces a comprehensive generator cost reduction of the microgrid system. It was evident from the results that generation cost was minimum when Time of Usage (TOU) based market pricing strategy was considered. Further, it was also established that dynamic grid participation was reduced 47% in the system generation cost for the same scenario compared to the case when the grid was operating passively. The statistical analysis endorses the improvements of GWOSCACSA over other algorithms presented in the state-of-art-literature. [ABSTRACT FROM AUTHOR]

This study proposes the application of an efficient and hybrid meta-heuristic algorithm of Harris Hawk-Particle Swarm Optimizer (HHOPSO) for solving voltage constrained reactive power planning (VCRPP) problem. The prime objective of present work is diminishing the transmission loss and overall operating cost coupled with retention of voltage consistency and enhanced congestion management in transmission lines. The efficacy of the proposed algorithm is tested on standard IEEE 57 bus test system with optimal transformer tap settings, reactive generation control, generator voltage control and optimal control of Var sources. The best location of Var sources is determined by Voltage Collapse Proximity Indicator (VCPI) method. Simulation results are generated under normal and variable reactive power loading condition which makes the reactive power planning problem more challenging and validates the robustness of the proposed algorithm. The results of proposed algorithm when compared with the other optimization algorithms surfaced in contemporary state of art literature yields superior solution in maintaining diversity and solution optimality. [ABSTRACT FROM AUTHOR]

Background: Postpartum Depression (PPD) is one of the least vocalized topics surrounding pregnancy and motherhood in India. The study aimed to assess the postpartum depression in women who had cesarean and normal vaginal deliveries. Materials and Methods: In this study, we identify postpartum depression in recently postpartum women and compare it in different maternal ages, modes of delivery (cesarean and vaginal), and sexes of the babies, since very few studies have explored these as risk factors. Data were obtained over six months from 210 women via their responses to the Edinburgh Postnatal Depression Scale (EPDS). An EPDS score of =7 out of 30 was set to determine postpartum depression, which was further classified as mild, moderate, or severe. Results: Total of 210 patients analyzed in the study out of which 157 (74.7%) exhibited PPD, which was more common in mothers aged between 19 and 27 years, and those who delivered via cesarean section. Mild depression was the most frequently occurring severity overall. Conclusion: Screening of PPD and providing suitable education should be encouraged during postpartum care or child-care visits for identifying and managing PPD, which in turn improves child development. [ABSTRACT FROM AUTHOR]

Background: The drug Finerenone, a selective the drug mineralocorticoid receptor antagonist, indicated for Chronic Kidney Disease (CKD) and Type 2 Diabetes. Recent researchers also found add on role in the management of resistant hypertension. So, this review article aims to provide an in-depth understanding of finerenone and the objective is to explore the mechanism of action, efficacy, and potential benefits of finerenone in treating (CKD) and heart failure with reduced ejection fraction (HFrEF), specifically in patients who have both type 2 diabetes (T2D) and CKD. Materials and Methods: A systematic literature search was done using IBM Micromedex, PubMed, Cochrane Library, and Scopus databases to identify relevant English-language articles published between 2000 and March 2023. Search terms included "Finerenone," "MRA," "Resistant Hypertension," "Finerenone Efficacy," and "Pharmacology of Finerenone." The selection criteria included clinical trials, randomized trials, and original articles, with references listed chronologically. Results: Finerenone's selective blockade of mineralocorticoid receptors counteracts the adverse effects of aldosterone, exhibiting anti-inflammatory and anti-fibrotic properties. Clinical trials consistently demonstrate its efficacy in reducing albuminuria, slowing CKD progression, and improving cardiovascular outcomes in patients with T2D and CKD. The recent approval of finerenone by the FDA for reducing the risk of death and abnormal cardiovascular events in adults with CKD and T2D with HFrEF highlights its therapeutic potential. Conclusion: Finerenone represents a pharmacological breakthrough in the management of resistant hypertension, offering a comprehensive therapeutic approach for patients with CKD and T2D. Its selective mineralocorticoid receptor antagonism, combined with anti-inflammatory and anti-fibrotic effects, shows promise in improving long-term renal and cardiovascular health. However, further research is needed to fully understand its long-term benefits, safety profile, and optimal utilization in the management of resistant hypertension. Finerenone's emergence provides new possibilities for patient care and signifies a significant advancement in the treatment of CKD and T2D, with the potential to enhance patient outcomes and quality of life. [ABSTRACT FROM AUTHOR]

• A metaheuristic approach called Modified Whale Optimization Algorithm (MWOA) is proposed. • Algorithms are tested on standard 23 Benchmark functions. • Application of the proposed algorithm in 1-phase transmission lines. Here six cases have been analyzed. • Application of the proposed algorithm in 3-phase transmission lines. Here another six cases have been analyzed. • Statistical test has been performed for 1-phase transmission and 3-phase transmission line. The overhead power line transmits and distributes electricity across large regions it has several conductors on poles. Power system stability analysis and state estimates need a thorough understanding of transmission line parameters. To compute the overhead AC transmission line parameters, authors have proposed a modified whale optimization algorithm based on levy flight from four perspectives: dimension selection, exploration controls, modified encircling prey, and candidate solution choice. The proposed work suggested modified whale optimization algorithms to calculate capacitance and inductance per unit length for single-phase and three-phase for the different number of bundle conductors. At first, the performance of the algorithm is evaluated and compared with different optimization techniques on 23 standard benchmark functions that are used to evaluate their abilities to discover optimum solutions. Then, the proposed technique is applied in determining optimal parameter settings of 1-phase and 3-phase overhead transmission lines while considering different combinations of bundle conductors for inductor and capacitor. From the results, it can be concluded that the MWOA technique provides more accuracy and reliability to obtain global or near-global optimal settings of control variables. Also, results reveal the proposed technique has the potent to solve real-world optimization problems and is competitive with recent methods. [ABSTRACT FROM AUTHOR]

The proposed work studies the frequency stability of the identified hybrid power network (HPS) model with the integration of RESs and ESDs. The research work depicted here includes load frequency issue pertaining to isolated mode of operations with uncertainties in power oscillations of wind and solar energy. The studied HPS model is constitute of three wind turbine generators, two solar thermal generators, three diesel engine generators, an aqua electrolyzer and two fuel‐cells as generating units while battery energy storage system, flywheel energy storage system and ultra‐capacitor as back‐up energy sources. A centralized control scheme using PID controller is employed for the controller design problem and its parameters are tuned by a nature inspired Quasi‐oppositional Harmony Search (QOHS) algorithm. The three scenarios as step change, step change with stochastic effects and firm model of wind velocity, solar radiation and load demand are studied for the load frequency control dynamic performance. The execution of suggested QOHS based PID controller is contrasted with the studied optimization techniques. It may be inferred that the RESs and ESDs feeding isolated loads are properly operated to attain the coveted level of system frequency by using the QOHS technique. [ABSTRACT FROM AUTHOR]