Lepton Flavor Violation in Economical 3-3-1 Model with Neutrino Singlets

Lepton flavor violating (LFV) decays of charged leptons $\mu\rightarrow e\gamma$  and SM-like Higgs boson $h\rightarrow \mu\tau$ are discussed in the framework of the  economical 3-3-1 model  adding three additional singlets neutrinos (E331$X_R$). We will show that the appearance of new neutrinos and charged Higgs bosons in this model can result in interesting regions of the parameter space, which satisfy  the recent experimental bound of $Br(\mu\rightarrow e\gamma)$  as well as give large $Br(h\rightarrow \mu\tau)\geq \mathcal{O}(10^{-7})$ . In these regions,  the charged Higgs boson mass lies within the range of $2-3$ TeV. Our results show that the LFV decays are important channels to distinguish the E331$X_R$  and the original economical (E331) models, which predicts suppressed LFV decay rates

Robust Adaptive Cerebellar Model Articulation Controller for 1-DOF Nonlaminated Active Magnetic Bearings

This paper presents a robust adaptive cerebellar model articulation controller (RACMAC) for 1-DOF nonlaminated active magnetic bearings (AMBs) to achieve desired positions for the rotor using a robust sliding mode control based. The dynamic model of 1-DOF nonlaminated AMB is introduced in fractional order equations. However, it is challenging to design a controller based on the model\u27s parameters due to undefined components and external disturbances such as eddy current losses in the actuator, external disturbance, variant parameters of the model while operating. In order to tackle the problem, RACMAC, which has a cerebellar model to estimate nonlinear disturbances, is investigated to resolve this problem. Based on this estimation, a robust adaptive controller that approximates the ideal and compensation controllers is calculated. The online parameters of the neural network are adjusted using Lyapunov\u27s stability theory to ensure the stability of system. Simulation results are presented to demonstrate the effectiveness of the proposed controller.The simulation results indicate that the CMAC multiple nonlinear multiple estimators are close to the actual nonlinear disturbance value, and the effectiveness of the proposed RACMAC method compared with the FOPID and SMC controllers has been studied previously

A Novel Self-organizing Fuzzy Cerebellar Model Articulation Controller Based Overlapping Gaussian Membership Function for Controlling Robotic System

This paper introduces an effective intelligent controller for robotic systems with uncertainties. The proposed method is a novel self-organizing fuzzy cerebellar model articulation controller (NSOFC) which is a combination of a cerebellar model articulation controller (CMAC) and sliding mode control (SMC). We also present a new Gaussian membership function (GMF) that is designed by the combination of the prior and current GMF for each layer of CMAC. In addition, the relevant data of the prior GMF is used to check tracking errors more accurately. The inputs of the proposed controller can be mixed simultaneously between the prior and current states according to the corresponding errors. Moreover, the controller uses a self-organizing approach which can increase or decrease the number of layers, therefore the structures of NSOFC can be adjusted automatically. The proposed method consists of a NSOFC controller and a compensation controller. The NSOFC controller is used to estimate the ideal controller, and the compensation controller is used to eliminate the approximated error. The online parameters tuning law of NSOFC is designed based on Lyapunov’s theory to ensure stability of the system. Finally, the experimental results of a 2 DOF robot arm are used to demonstrate the efficiency of the proposed controller

Red light emission of Mn doped beta-tricalcium phosphate -Ca3(PO4)2

This paper is the first report on the red light emission of manganese (Mn) doped beta-tricalcium phosphate (b-Ca3(PO4)2, TCP) synthesis by co-precipitation method followed by thermal annealing. The annealed Mn doped TCP phosphor showed dominant spheres with a diameter of about 500 nm. The influences of the Mn concentration, annealing temperature, and atmospheres on the photoluminescence intensities of the phosphors were investigated and the results indicate that the annealing temperatures and Mn concentrations are the main factors. The phosphor showed visible emission peaks appeared at about 660 nm and 580 nm results in from the 4T1-6A1 transitions within Mn2+ ion. The Mn-TCP phosphor may serve as a candidate for light-emitting diode application in agriculture lighting. Keywords. Hydroxyapatite; manganese; luminescence; tricalcium phosphate

A Fast and Close-to-Optimal Receding Horizon Control for Trajectory Generation in Dynamic Environments

This paper presents a new approach for the optimal trajectory planning of nonlinear systems in a dynamic environment. Given the start and end goals with an objective function, the problem is to find an optimal trajectory from start to end that minimizes the objective while taking into account the changes in the environment. One of the main challenges here is that the optimal control sequence needs to be computed in a limited amount of time and needs to be adapted on-the-fly. The control method presented in this work has two stages: the first-order gradient algorithm is used at the beginning to compute an initial guess of the control sequence that satisfies the constraints but is not yet optimal; then, sequential action control is used to optimize only the portion of the control sequence that will be applied on the system in the next iteration. This helps to reduce the computational effort while still being optimal with regard to the objective; thus, the proposed approach is more applicable for online computation as well as dealing with dynamic environments. We also show that under mild conditions, the proposed controller is asymptotically stable. Different simulated results demonstrate the capability of the controller in terms of solving various tracking problems for different systems under the existence of dynamic obstacles. The proposed method is also compared to the related indirect optimal control approach and sequential action control in terms of cost and computation time to evaluate the improvement of the proposed method

A Fast and Close-to-Optimal Receding Horizon Control for Trajectory Generation in Dynamic Environments

This paper presents a new approach for the optimal trajectory planning of nonlinear systems in a dynamic environment. Given the start and end goals with an objective function, the problem is to find an optimal trajectory from start to end that minimizes the objective while taking into account the changes in the environment. One of the main challenges here is that the optimal control sequence needs to be computed in a limited amount of time and needs to be adapted on-the-fly. The control method presented in this work has two stages: the first-order gradient algorithm is used at the beginning to compute an initial guess of the control sequence that satisfies the constraints but is not yet optimal; then, sequential action control is used to optimize only the portion of the control sequence that will be applied on the system in the next iteration. This helps to reduce the computational effort while still being optimal with regard to the objective; thus, the proposed approach is more applicable for online computation as well as dealing with dynamic environments. We also show that under mild conditions, the proposed controller is asymptotically stable. Different simulated results demonstrate the capability of the controller in terms of solving various tracking problems for different systems under the existence of dynamic obstacles. The proposed method is also compared to the related indirect optimal control approach and sequential action control in terms of cost and computation time to evaluate the improvement of the proposed method

Cardiogenic Shock Secondary to Dynamic Left Ventricular Outflow Tract Obstruction and Apical Ballooning after Nonmitral Cardiovascular Surgery

Background. The dynamic obstruction of the left ventricular outflow tract (LVOT) is a well-known complication in mitral annuloplasty but rarely seen in nonmitral cardiovascular surgery. The dynamic LVOT obstruction can lead to hemodynamic instability, even shock and the treatment is significantly different from the standard approach. Case Presentation. We reported a case of low cardiac output syndrome (LCOS) with severe mitral regurgitation (MR), dramatically reduced left ventricular ejection fraction (LVEF) after coronary artery bypass grafting in a 72-year-old female requiring an escalation of inotropic support, volume restriction, and mechanical support. The detailed echocardiography combined with lung ultrasound revealed a dynamic systolic anterior movement of the anterior mitral leaflet (SAM), apical ballooning, and no significant lung congestion. Intravenous fluids were given, diuretics withdrawn, inotrope discontinued, and vasopressors uptitrated. The dynamic SAM was rapidly relieved, the hemodynamics was stabilized, and the LVEF was improving. The patient was discharged in good condition without residual LVOT obstruction and trace MR. Conclusion. We strongly suggest that a detailed echocardiography should be performed in any patient who presents in shock to rule out a dynamic LVOT obstruction. Lung ultrasound should be a routine examination in addition to echocardiography. Once SAM is detected, treatment should be based on volume expansion, inotrope discontinuation, and a careful afterload increasing

Robust Adaptive Cerebellar Model Articulation Controller for 1-DOF Nonlaminated Active Magnetic Bearings

This paper presents a robust adaptive cerebellar model articulation controller (RACMAC) for 1-DOF nonlaminated active magnetic bearings (AMBs) to achieve desired positions for the rotor using a robust sliding mode control based. The dynamic model of 1-DOF nonlaminated AMB is introduced in fractional order equations. However, it is challenging to design a controller based on the model's parameters due to undefined components and external disturbances such as eddy current losses in the actuator, external disturbance, variant parameters of the model while operating. In order to tackle the problem, RACMAC, which has a cerebellar model to estimate nonlinear disturbances, is investigated to resolve this problem. Based on this estimation, a robust adaptive controller that approximates the ideal and compensation controllers is calculated. The online parameters of the neural network are adjusted using Lyapunov's stability theory to ensure the stability of system. Simulation results are presented to demonstrate the effectiveness of the proposed controller.The simulation results indicate that the CMAC multiple nonlinear multiple estimators are close to the actual nonlinear disturbance value, and the effectiveness of the proposed RACMAC method compared with the FOPID and SMC controllers has been studied previously