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This study investigates the critical behavior analysis and predicting magnetocaloric properties of La0.6-xGdxSr0.4MnO3 manganites, focusing on the impact of varying gadolinium (Gd) doping levels (x = 0, 0.0125, 0.05, and 0.10). Using modified Arrott plots (MAPs) and the Kouvel–Fisher method, the critical exponents γ and β were determined, yielding values that indicate how Gd content influences magnetic phase transitions. Additionally, the magnetocaloric effect (MCE) was analyzed to assess the magnetic entropy change − Δ S M (T) and the Temperature-Averaged Entropy Change (TEC) across different magnetic field changes. The results show that increasing Gd doping enhances the magnetocaloric response, suggesting potential applications in magnetic refrigeration. Overall, the study provides insights into optimizing these manganites for applications in high-temperature sensors, spintronics, and magnetic cooling. Highlights: Using modified Arrott plots (MAPs) and the Kouvel–Fisher method, the critical exponents γ and β of La0.6-xGdxSr0.4MnO3 (x = 0, 0.0125, 0.05, and 0.10) manganites were derived. The magnetocaloric effect (MCE) was analyzed to assess the magnetic entropy change − Δ S M (T) and the Temperature-Averaged Entropy Change (TEC) across different magnetic field changes. [ABSTRACT FROM AUTHOR]

To decrease Candidatus Liberibacter asiaticus titer and increase the productive life of infected trees, thermal treatment of orange trees was proposed.  A moving greenhouse was developed to cover single trees during the summer of 2012.  Four trees (~ 2.5×2.5×2.5 m) were treated, one tree per day, during the months of September (trees T1 through T3) and October (tree T4).  From each tree, three symptomatic branches were sampled to determine microbial kill before (0 h) and at 2, 3, 4, and 5 h during the treatment.  Temperature distribution throughout the canopy and on the sampled branches was also recorded.  Maximal temperatures in the ranges 50 to 53 °C were reached at the top (2.4 m) of the canopy whereas at the bottom of the canopy (i.e., 0.6 m) maximal temperatures ranged from 36 to 43 °C.  Due to varied micro-meteorological conditions during the treatment, temperatures of the T1 through T4 sampled branches reached above 40⁰C for 217, 166, 35, 228 min, respectively.  For T1, T2 and T4 trees, average temperatures of the sampled branches reached above 45 °C for 87, 35, and 49 min or more.  Attempts to quantitatively determine microbial kill by determining percent live bacteria at selected time intervals during thermal treatment was unreliable due to the very uneven distribution of initial proportion of live-to-dead bacteria and analysis variability.  However, overall, after thermal treatments, live microbial populations decreased.  These findings indicate that adequate thermal treatment of trees required forced convection air flow and supplemental heating.

A novel nonlinear controller is proposed to track active and reactive power for a Brushless Doubly-Fed Induction Generator (BDFIG) wind turbine. Due to nonlinear dynamics and the presence of parametric uncertainties and perturbations in this system, sliding mode control is employed. To generate a smooth control signal, dynamic sliding mode method is used. Uncertainties bound is not required in the suggested algorithm, since the adaptive gain in the controller relation is used in this study. Convergence of the sliding variable to zero and adaptive gain to the uncertainty bound are verified using Lyapunov stability theorem. The proposed controller is evaluated in a comprehensive simulation on the BDFIG model. Moreover, output performance of the proposed control algorithm is compared to the conventional and second order sliding mode and proportional-integral-derivative (PID) controllers. [ABSTRACT FROM AUTHOR]