In this study, we examined the indirect effects of anxiety on glycated hemoglobin (A1C) via automatic negative thinking and diabetes distress among adolescents with type 1 diabetes (T1D) during the follow-up interval of a randomized controlled trial of an intervention targeting resilience promotion/depression prevention.

Adolescents (N=264) participating in the Supporting Teen Problem Solving clinical trial were included and assessed at 8, 12, 16 and 28 months postbaseline. A serial, double-mediation model was used to examine path effects from anxiety to A1C through automatic negative thinking, through diabetes distress and through both automatic negative thinking and diabetes distress. Relevant demographic and clinical covariates were included.

Anxiety significantly predicted increases in both automatic negative thinking and diabetes distress. Automatic negative thinking was not found to mediate the association between anxiety and A1C, but diabetes distress did mediate the association. The double-mediad as a mediator of glycemic variability in anxious youth with T1D.

The Timing of Initiation of Continuous Glucose Monitoring in Established Pediatric Diabetes (CGM TIME) Trial is a multicenter, randomized controlled trial in children with type 1 diabetes, comparing simultaneous pump and CGM with CGM initiation 6 months later (Paradigm, Veo, Enlite Sensor, Medtronic Canada). This study addresses the ability of SOCRATES (Stages Of Change Readiness And Treatment Eagerness Scale) to classify children and parents into distinct motivational stages and identify the stages’ association with glycated hemoglobin (A1C) at trial entry and outcomes 6 months after CGM initiation.

Ninety-eight of 99 eligible children 10 to 18 years of age and 137 of 141 eligible parents completed SOCRATES at trial entry and 6 months later. Poziotinib Parent-child agreement for motivational stage was determined by weighted kappa. Linear regression was used to examine association between motivational stage and i) A1C at trial entry and ii) change in A1C and CGM adherence 6 months after CGM initiation.

More than 8glycemic control at trial entry, it did not predict future diabetes-related behaviour or A1C.The moving-gimbal effect (MGE) is an important factor that limits the torque accuracy provided by magnetically suspended control moment gyroscope. This work addresses the issues concerning the dynamic behavior of active magnetic bearing (AMB) systems under MGE. First, the dynamics modeling of AMB-rotor system is established. Then, a linear extended state observer (LESO) based control is proposed to suppress the MGE. The dynamic response of PID control is significantly improved by replacing the integral term with LESO. The LESO gain tuning procedure is performed by analyzing the pole-zero assignment that determines the dynamic performance. The stability of LESO is proved by the convergence of estimation error dynamics. Finally, the proposed method shows effective suppression on MGE with less power consumptions in experiment.This paper considers the trajectory tracking problem of an underactuated underwater vehicle actuated by control moment gyros (CMGs) in three-dimensional (3D) space, with the constraints from input saturation, partial parameter uncertainty and unknown external disturbance. First, utilizing a physical translation of the motion equations, the overall system can be decomposed to an input decoupling system. Then a modified virtual velocity guidance law is derived to transform the tracking error signals into the controllable velocity signals. Subsequently, the Gaussian error function is employed to update the common saturation model. To avoid complex derivations of the virtual control signals, first-order sliding mode differentiator is explored in the dynamic control layer. Then, the adaptive neural network (NN) control method is introduced into the backstepping procedure to account for nonlinear uncertainties and bounded disturbances. Among this, the constrained steering law is used to steer the CMG system to avoid its inherent singularity and fulfill the global tracking control. It is proved that the proposed controller can guarantee all closed-loop signals converge to a small neighborhood of the origin. Finally, two case studies are presented to illustrate the tracking performance of the proposed design.This paper proposes a method that combines active disturbance rejection control (ADRC) and adaptive fuzzy sliding mode control (AFSMC), which is beneficial for the optoelectronic platform to enhance the target tracking capability. A servo system model based on the LuGre friction is first established. The AFSMC controller estimates the unknown part of the platform, and the fuzzy approximator can reduce chattering. Then, an ADRC controller based on Back-Propagation neural network tuning is designed and compared with the empirical method, which makes the system’s tracking accuracy higher. Lyapunov’s theorem and Barbara’s lemma are forceful methods to prove engineering stability. Simulations illustrate that the influence of external disturbances on the optoelectronic platform can be suppressed, thereby enhancing the disturbance isolation of the controller.This paper devotes to the three-dimensional formation problem of multi-robots in obstacle environment. Given the desired formation pattern and the group trajectory, it is formulated as obtaining the control inputs of robots so that the formation errors converge to zero gradually with obstacle/collision avoidance subject to state and input constraints. The well-known nonlinear model predictive control (NMPC) can be utilized as the solution framework due to its stability and robustness according with the reference state vector. Particularly, the null-space-based modulated reference trajectory generator is proposed to modulate the reference state vector of each robot. The original reference velocity, obtained from the Lyapunov stability theory, will be modulated quantitatively in the presence of each obstacle, and then the modulated velocities are integrated effectively on the basis of null space. From the perspective of trajectory generator, it is proven that the robots will avoid obstacles or collision without violating the stability of formation system.