A Visit-Associated Logistics Framework Describing Challenges Faced by Caregivers of Older Adults.

Unpaid family caregivers are assuming increasing levels of care as the healthcare system prioritizes aging in place over institutionalized care. Among their many responsibilities, coordinating in-person clinical visits is a critically important yet understudied area. This logistical aspect of caregiving for older adults is complex as it is influenced by many different medical-psycho-social factors.

Resilient consensus control for networked robotic manipulators under actuator faults and deception attacks.

Resilient consensus control refers to a system's ability to maintain agreement among its components despite disruptions, failures, or malicious attacks. This paper introduces a resilient control algorithm for a group of robotic manipulators to achieve leader-follower consensus within their workspace, despite actuator faults and deception attacks affecting exchanged signals. The proposed approach leverages adaptive control algorithms to develop the control laws.

Supporting Educational Excellence in Diversity (SEED): faculty development and allyship.

Introduction: Bias, privilege, microaggressions, and other forms of mistreatment negatively impact students' learning, professional development, wellness, and identity. Supporting Educational Excellence in Diversity (SEED) is an innovative faculty development curriculum co-founded and co-designed by medical students/trainees. SEED is unique given it provides vital yet practical communication tools and strategies to support cultural humility when navigating critical conversations related to diversity, inclusion, and harm.

Factors influencing trust in algorithmic decision-making: an indirect scenario-based experiment.

Algorithms are involved in decisions ranging from trivial to significant, but people often express distrust toward them. Research suggests that educational efforts to explain how algorithms work may help mitigate this distrust. In a study of 1,921 participants from 20 countries, we examined differences in algorithmic trust for low-stakes and high-stakes decisions.

Optimal nonlinear PID TSK3DCMAC controller based on balancing composite motion optimization for ballbot with external forces.

This paper proposes an innovative approach to address the challenges of dynamic balance and external disturbances in ballbot systems, overcoming the limitations of conventional Proportional Integral Derivative (PID) controllers and their variants in handling highly nonlinear dynamics and external forces. Traditional PID controllers and their variants often have difficulty adapting to complex, real-time dynamic systems, leading to performance degradation under varying conditions. A nonlinear PID controller-based Takagi-Sugeno-Kang 3D Cerebellar Model Articulation Controller (TSK3DCMAC) is introduced to overcome these shortcomings.