Trichinosis is a serious parasitic zoonotic disease caused mainly by Trichinella spiralis. The used drugs for treatment of trichinosis showed limited bioavailability and high degree of resistance. Moreover, they have a very poor effect in treatment of encysted larvae. Therefore, there is a need for development of new agents which help in improving the bioavailability of the used drugs and enable them to reach different tissues. This study was designed to assess the use of chitosan nanoparticles (CSNPs) in conjugation with full and half dose albendazole (ABZ) in treatment of intestinal and muscular trichinosis. Albino mice (84 mice) were used to evaluate the efficacy of drugs and divided into seven groups; I: control, II: ABZ (50 mg/kg) treated, III: ABZ (25 mg/kg) treated, IV: ABZ (50 mg/kg) conjugated CSNPs treated, V: ABZ (25 mg/kg) conjugated CSNPs treated, VI: CS treated and VII: CSNPs treated. Parasitological and histopathological examinations were used to evaluate the therapeutic efficacy of the used drugs. Results showed significant reduction of adult Trichinella extracted from intestine of all ABZ treated groups either conjugated or not with the highest reduction rate in group IV followed by group V with percentage of reduction of 99.33% and 98.11%, respectively and marked improvement of histopathological examination. Also, results showed significant reduction of Trichinella larvae extracted from muscles of group IV, V and VII with the highest reduction rate in group IV with percentage of reduction of 100% in muscle larvae and marked improvement of histopathological examination. It was concluded that albendazole full dose conjugated chitosan nanoparticles can be a good candidate drug for treating both intestinal and muscular trichinosis.

Erigeron bonariensis is widely distributed throughout the world's tropics and subtropics. In folk medicine, E. bonariensis has historically been used to treat head and brain diseases. Alzheimer's disease (AD) is the most widespread form of dementia initiated via disturbances in brain function. Herein, the neuroprotective effect of the chemically characterized E. bonariensis ethanolic extract is reported for the first time in an AD animal model. Chemical profiling was conducted using UPLC-ESI-MS analysis. Female rats underwent ovariectomy (OVX) followed by 42 days of D-galactose (D-Gal) administration (150 mg/kg/day, i.p) to induce AD. The OVX/D-Gal-subjected rats received either donepezil (5 mg/kg/day) or E. bonariensis at 50, 100, and 200 mg/kg/day, given 1 h prior to D-Gal. UPLC-ESI-MS analysis identified 42 chemicals, including flavonoids, phenolic acids, terpenes, and nitrogenous constituents. Several metabolites, such as isoschaftoside, casticin, velutin, pantothenic acid, xanthurenic acid, C18-sphingosine, linoleamide, and erucamide, were reported herein for the first time in Erigeron genus. Treatment with E. bonariensis extract mitigated the cognitive decline in the Morris Water Maze test and the histopathological alterations in cortical and hippocampal tissues of OVX/D-Gal-subjected rats. Moreover, E. bonariensis extract mitigated OVX/D-Gal-induced Aβ aggregation, Tau hyperphosphorylation, AChE activity, neuroinflammation (NF-κBp65, TNF-α, IL-1β), and apoptosis (Cytc, BAX). Additionally, E. bonariensis extract ameliorated AD by increasing α7-nAChRs expression, down-regulating GSK-3β and FOXO3a expression, and modulating Jak2/STAT3/NF-ĸB p65 and PI3K/AKT signaling cascades. These findings demonstrate the neuroprotective and memory-enhancing effects of E. bonariensis extract in the OVX/D-Gal rat model, highlighting its potential as a promising candidate for AD management.

Erigeron bonariensis is widely distributed throughout the world's tropics and subtropics. In folk medicine, E. bonariensis has historically been used to treat head and brain diseases. Alzheimer's disease (AD) is the most widespread form of dementia initiated via disturbances in brain function. Herein, the neuroprotective effect of the chemically characterized E. bonariensis ethanolic extract is reported for the first time in an AD animal model. Chemical profiling was conducted using UPLC-ESI-MS analysis. Female rats underwent ovariectomy (OVX) followed by 42 days of D-galactose (D-Gal) administration (150 mg/kg/day, i.p) to induce AD. The OVX/D-Gal-subjected rats received either donepezil (5 mg/kg/day) or E. bonariensis at 50, 100, and 200 mg/kg/day, given 1 h prior to D-Gal. UPLC-ESI-MS analysis identified 42 chemicals, including flavonoids, phenolic acids, terpenes, and nitrogenous constituents. Several metabolites, such as isoschaftoside, casticin, velutin, pantothenic acid, xanthurenic acid, C18-sphingosine, linoleamide, and erucamide, were reported herein for the first time in Erigeron genus. Treatment with E. bonariensis extract mitigated the cognitive decline in the Morris Water Maze test and the histopathological alterations in cortical and hippocampal tissues of OVX/D-Gal-subjected rats. Moreover, E. bonariensis extract mitigated OVX/D-Gal-induced Aβ aggregation, Tau hyperphosphorylation, AChE activity, neuroinflammation (NF-κBp65, TNF-α, IL-1β), and apoptosis (Cytc, BAX). Additionally, E. bonariensis extract ameliorated AD by increasing α7-nAChRs expression, down-regulating GSK-3β and FOXO3a expression, and modulating Jak2/STAT3/NF-ĸB p65 and PI3K/AKT signaling cascades. These findings demonstrate the neuroprotective and memory-enhancing effects of E. bonariensis extract in the OVX/D-Gal rat model, highlighting its potential as a promising candidate for AD management.

In fast-growing isolated microgrids (IMGs), load frequency control (LFC) ensures optimal power quality for end
users. Stochastic grids, notably with renewable energy resources (RESs), require robust and intelligently designed LFC schemes. Thus, this research presents a novel cascade-loop controller combining a fractional order proportional derivative with a filter and a fractional order-proportional tilt integral derivative (FPDN-FPTID)
to improve LFC for single and multi-area IMGs. Recent dandelion optimization adjusts FPDN-FPTID controller
settings. Anti-windup keeps the controller out of the non-linear zone for low inertia IMGs. It concerns various
sources’ maximum generating rates. The two-area IMG model shows its potential and scalability. Extensive
MATLAB/Simulink simulations show that the FPDN-FPTID controller outperforms numerous published controllers, either single or cascade-loop, in minimum error criteria, undershoots/ overshoots/settling times, frequency, and tie-line power deviation following load and RES variations. Finally, the sensitivity study indicates
the suggested controller stabilizes the system despite ±25 % parameter changes.

Load frequency control (LFC) is vital for isolated microgrids (IMGs), especially when uncertain renewable energy sources (RESs) are present. Enhancing LFC schemes relies mainly on three tracks. Adding new resources to IMG structures is the first track, designing novel controller structures for LFC schemes is the second, and the third is improving controller tuning procedures in the LFC schemes. This research suggests an innovative multi-objective formula (MOF) for controller tuning that combines a novel error criterion termed the integral-square time absolute error of frequency change with the integral-square of IMG controllers' signals. Tested IMG includes multi-sources of diesel engine generators, fuel cells, battery energy storage technologies, and RESs (like photovoltaic and wind turbines). The proposed MOF tuning is evaluated compared to four different objective functions, which are the integral-absolute error (IAE), integral-time absolute error (ITAE), integral-square error (ISE), and integral-time square error (ITSE). The proportional-integral-derivative (PID), fractional-order, and cascade PID controllers are implemented to appraise the proposed MOF extensively against all these single objectives. Statistical analyses are accomplished comprehensively to verify the effectiveness of the artificial rabbits' optimization algorithm (ARO) in competition with other recent optimization algorithms to tune different controllers utilized in the LFC schemes of the examined IMG based on tested objectives. Therefore, ARO is applied to optimize controller settings by combining system nonlinearities with IMG sources' maximal generation rate constraints. The comparative analysis considers settling times, overshoots, IAE, ITAE, ISE, and ITSE performance indices. MATLAB/Simulink simulations confirmed the ability of the suggested MOF tuning to stabilize the system and keep improving performance indices, significantly attaining the minimum settling time even for massive three-type load fluctuations. The first type is step disturbances ranging between 0.1 and 0.25 p.u, the second is varying step disturbances every 5 s, and the third is severe dynamic random load shifts from −0.2 to 0.2 p.u. In addition, the MOF outperforms other competitors' tuning formulas while adding fluctuations of RESs with load disturbances. Furthermore, the robustness analysis is conducted for the applied controllers based on the proposed MOF tuning approach by changing the IMG nominal parameters with ±25 % and adding system nonlinearities. The analysis ensured its efficacy in preserving system stability. Finally, the stability test in the frequency domain using the MATLAB/control design tool verified system stability when different LFC controllers were tuned based on the proposed MOF tuning.

Load frequency control (LFC) is vital for isolated microgrids (IMGs), especially when uncertain renewable energy sources (RESs) are present. Enhancing LFC schemes relies mainly on three tracks. Adding new resources to IMG structures is the first track, designing novel controller structures for LFC schemes is the second, and the third is improving controller tuning procedures in the LFC schemes. This research suggests an innovative multi-objective formula (MOF) for controller tuning that combines a novel error criterion termed the integral-square time absolute error of frequency change with the integral-square of IMG controllers' signals. Tested IMG includes multi-sources of diesel engine generators, fuel cells, battery energy storage technologies, and RESs (like photovoltaic and wind turbines). The proposed MOF tuning is evaluated compared to four different objective functions, which are the integral-absolute error (IAE), integral-time absolute error (ITAE), integral-square error (ISE), and integral-time square error (ITSE). The proportional-integral-derivative (PID), fractional-order, and cascade PID controllers are implemented to appraise the proposed MOF extensively against all these single objectives. Statistical analyses are accomplished comprehensively to verify the effectiveness of the artificial rabbits' optimization algorithm (ARO) in competition with other recent optimization algorithms to tune different controllers utilized in the LFC schemes of the examined IMG based on tested objectives. Therefore, ARO is applied to optimize controller settings by combining system nonlinearities with IMG sources' maximal generation rate constraints. The comparative analysis considers settling times, overshoots, IAE, ITAE, ISE, and ITSE performance indices. MATLAB/Simulink simulations confirmed the ability of the suggested MOF tuning to stabilize the system and keep improving performance indices, significantly attaining the minimum settling time even for massive three-type load fluctuations. The first type is step disturbances ranging between 0.1 and 0.25 p.u, the second is varying step disturbances every 5 s, and the third is severe dynamic random load shifts from −0.2 to 0.2 p.u. In addition, the MOF outperforms other competitors' tuning formulas while adding fluctuations of RESs with load disturbances. Furthermore, the robustness analysis is conducted for the applied controllers based on the proposed MOF tuning approach by changing the IMG nominal parameters with ±25 % and adding system nonlinearities. The analysis ensured its efficacy in preserving system stability. Finally, the stability test in the frequency domain using the MATLAB/control design tool verified system stability when different LFC controllers were tuned based on the proposed MOF tuning.

Load frequency control (LFC) is vital for isolated microgrids (IMGs), especially when uncertain renewable energy sources (RESs) are present. Enhancing LFC schemes relies mainly on three tracks. Adding new resources to IMG structures is the first track, designing novel controller structures for LFC schemes is the second, and the third is improving controller tuning procedures in the LFC schemes. This research suggests an innovative multi-objective formula (MOF) for controller tuning that combines a novel error criterion termed the integral-square time absolute error of frequency change with the integral-square of IMG controllers' signals. Tested IMG includes multi-sources of diesel engine generators, fuel cells, battery energy storage technologies, and RESs (like photovoltaic and wind turbines). The proposed MOF tuning is evaluated compared to four different objective functions, which are the integral-absolute error (IAE), integral-time absolute error (ITAE), integral-square error (ISE), and integral-time square error (ITSE). The proportional-integral-derivative (PID), fractional-order, and cascade PID controllers are implemented to appraise the proposed MOF extensively against all these single objectives. Statistical analyses are accomplished comprehensively to verify the effectiveness of the artificial rabbits' optimization algorithm (ARO) in competition with other recent optimization algorithms to tune different controllers utilized in the LFC schemes of the examined IMG based on tested objectives. Therefore, ARO is applied to optimize controller settings by combining system nonlinearities with IMG sources' maximal generation rate constraints. The comparative analysis considers settling times, overshoots, IAE, ITAE, ISE, and ITSE performance indices. MATLAB/Simulink simulations confirmed the ability of the suggested MOF tuning to stabilize the system and keep improving performance indices, significantly attaining the minimum settling time even for massive three-type load fluctuations. The first type is step disturbances ranging between 0.1 and 0.25 p.u, the second is varying step disturbances every 5 s, and the third is severe dynamic random load shifts from −0.2 to 0.2 p.u. In addition, the MOF outperforms other competitors' tuning formulas while adding fluctuations of RESs with load disturbances. Furthermore, the robustness analysis is conducted for the applied controllers based on the proposed MOF tuning approach by changing the IMG nominal parameters with ±25 % and adding system nonlinearities. The analysis ensured its efficacy in preserving system stability. Finally, the stability test in the frequency domain using the MATLAB/control design tool verified system stability when different LFC controllers were tuned based on the proposed MOF tuning.