79 research outputs found
Facile transformation of aromatic aldehydes to acids mediated by tetraethylammonium superoxide
805-80
Electrogenerated superoxide induced oxidation of thiols and disulfide interchange: A functional group approach to biomimetic study
411-41
Oxidative cleavage of ɑ-diketones using tetraethylammonium bromide as phase transfer catalyst
88-9
Modified African Buffalo Optimization for Strategic Integration of Battery Energy Storage in Distribution Networks
This article presents a two-layer optimization scheme for simultaneous optimal allocation of wind turbines (WTs) and battery energy storage systems (BESSs) in power distribution networks. The prime objective of this formulation is to maximize the renewable hosting capacity of the system. For outer-layer, a new objective function is developed by combining multiple objectives such as annual energy loss in feeders, back-feed power, BESSs conversion losses, node voltage deviation, and demand fluctuations caused by renewables subject to various system security and reliability constraints. Furthermore, a modified variant of African buffalo optimization (ABO) introduced to overcome some of the limitations observed in its standard variant. The proposed modifications are first validated and then introduced for simultaneous optimal integration of multiple distributed energy resources in distribution systems. The proposed modified ABO is employed to determine the optimization variables of outer-layer. Whereas, a heuristic is proposed to solve the inner-layer optimization problem aiming to determine the optimal dispatch of BESSs suggested by outer-layer optimization. By considering the high investment and operating cost of BESSs, minimum energy storage capacity has been ensured during the planning stage. To present the efficacy of developed model, it is implemented on a 33-bus, benchmark test distribution system for various test cases. The comparative simulation results show that the proposed optimization model and modified ABO is very promising to improve the performance of active distribution systems
Antikonvulzivno djelovanje Schiffovih baza- derivata isatina
Schiff bases of N-methyl and N-acetyl isatin derivatives with different aryl amines have been synthesized and screened for anticonvulsant activities against maximal electroshock (MES) and subcutaneous metrazole (ScMet). N-methyl-5-bromo-3-(p-chlorophenylimino) isatin 2 exhibited anticonvulsant activity in MES and ScMet with LD50 > 600 mg kg-1, showing better activity than the standard drugs phenytoin, carbamazepine and valproic acid. Thus, compound 2 may be chosen as a prototype for development of new anticonvulsants.Schiffove baze N-metil i N-acetil derivata izatina s različitim aromatskim aminima sintetizirane su i ispitane na sposobnost suzbijanja konvulzija uzrokovanih elektrošokom (MES) i subkutanom primjenom metrazola (ScMet). N-metil-5-bromo-3-(p-klorofenilimino) izatin 2 pokazao je nisku neurotoksičnost i jače antikonvulzivno djelovanje nego standardni antikonvulzivi fenitoin, karbamazepin i valproična kiselina. Zbog toga se spoj 2 može smatrati prototipom za razvoj novih antikonvulziva
Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks
The optimal integration of distributed energy resources (DERs) is a multiobjective and complex combinatorial optimization problem that conventional optimization methods cannot solve efficiently. This paper reviews the existing DER integration models, optimization and multi-criteria decision-making approaches. Further to that, a recently developed monarch butterfly optimization method is introduced to solve the problem of DER mix in distribution systems. A new multiobjective DER integration problem is formulated to find the optimal sites, sizes and mix (dispatchable and non-dispatchable) for DERs considering multiple key performance objectives. Besides, a hybrid method that combines the monarch butterfly optimization and the technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to solve the formulated large-scale multi-criteria decision-making problem. Whilst the meta-heuristic optimization method generates non-dominated solutions (creating Pareto-front), the TOPSIS approach selects that with the most promising outcome from a large number of alternatives. The effectiveness of this approach is verified by solving single and multiobjective dispatchable DER integration problems over the benchmark 33-bus distribution system and the performance is compared with the existing optimization methods. The proposed model of DER mix and the optimization technique significantly improve the system performance in terms of average annual energy loss reduction by 78.36%, mean node voltage deviation improvement by 9.59% and average branches loadability limits enhancement by 50%, and minimized the power fluctuation induced by 48.39% renewable penetration. The proposed optimization techniques outperform the existing methods with promising exploration and exploitation abilities to solve engineering optimization problems
Hybrid Elephant Herding and Particle Swarm Optimizations for Optimal DG Integration in Distribution Networks
In this article, the amalgamation of two well-established meta-heuristic optimization methods is presented to solve the multi-objective distributed generation (DG) allocation problem of distribution systems. To overcome some of the shortcomings of newly developed elephant herding optimization (EHO), an improvement is suggested and then, a prominent feature of particle swarm optimization is introduced to the modified version of EHO. The suggested modifications are validated by solving a single objective DG integration problem where various performance parameters of the proposed hybrid method are compared with their individual standard variants. After validation, the proposed technique is exploited to solve a multi-objective DG allocation problem of distribution systems, aiming to minimize power loss and node voltage deviation while simultaneously maximizing the voltage stability index of three benchmark distribution systems namely, 33-bus, 69-bus and 118-bus. The obtained simulation results are further compared with that of the same available in the existing literature. This comparison reveals that the proposed hybrid approach is promising to solve the multi-objective DG integration problem of distribution systems as compared to many existing methods
Modified Dragonfly Optimisation for Distributed Energy Mix in Distribution Networks
This article presents a two-stage optimization model aiming to determine optimal energy mix in distribution networks, i.e., battery energy storage, fuel cell, and wind turbines. It aims to alleviate the impact of high renewable penetration on the systems. To solve the proposed complex optimization model, a standard variant of the dragonfly algorithm (DA) has been improved and then applied to find the optimal mix of distributed energy resources. The suggested improvements are validated before their application. A heuristic approach has also been introduced to solve the second stage problem that determines the optimal power dispatch of battery energy storage as per the size suggested by the first stage. The proposed framework was implemented on a benchmark 33-bus and a practical Indian 108-bus distribution network over different test cases. The proposed model for energy mix and modified DA technique has significantly enhanced the operational performance of the network in terms of average annual energy loss reduction, node voltage profiles, and demand fluctuation caused by renewables
Identification of Clinical Immunological Determinants in Asymptomatic VL and Post Kala-azar Dermal Leishmaniasis Patients
Background: Visceral Leishmaniasis (VL) caused by protozoa belonging to the genus Leishmania, usually have anthroponotic mode of transmission and is issue of great public health importance in Indian subcontinent. Asymptomatic cases of VL and PKDL are subject of keen interest to find their role in the transmission of VL in epidemic areas. We evaluated the immunological cytokine determinants expressed in most clinical suspects of asymptomatic VL and PKDL (IL-10, IFN-γ, and TNF-α).
Methods: Eighty-four participants were included at RMRIMS, Patna, India in 2016-17 out of which 64 asymptomatic individual positive for rK-39, without sign and symptoms of VL; 15 PKDL patient’s with past history of VL and 5 endemic healthy subjects were recruited from VL endemic areas. DAT and quantitative assessment of plasma cytokines was determined from the blood samples collected in a plain and sodium-EDTA vacutainer respectively from the subjects.
Results: The mean level of IL-10 in DATposLOW of asymptomatic VL and PKDL was significantly higher than endemic healthy (P<0.05). The cytokine polarization index (IFN-γ versus IL-10) was significantly low in PKDL cases compared with asymptomatic VL cases in DATposLOW titre (P<0.05). This index was low again but statistically not significant in PKDL than in asymptomatic VL when TNF-α was considered against IL-10. The ratio of IFN-γ: IL-10 and TNF-α: IL-10 was observed decreased both in asymptomatic VL and PKDL cases than in healthy from endemic areas.
Conclusion: Collectively we surmise from our data that asymptomatic VL can also play an important role like PKDL in transmission of VL
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