https://www.selleckchem.com/products/OSI-906.html A vast literature exists on doctorally-prepared RNs in academia, but little is known about those in practice settings. The purpose of this study was to explore demographic, educational, and employment characteristics, as well as practice patterns and professional accomplishments of doctorally-prepared RNs in one practice setting. Survey of approximately 100 doctorally-prepared RNs in an integrated health system were surveyed. Doctors of Nursing Practice (DNPs) outnumber PhDs three to one in the institution. Several statistically significant differences exist between them DNPs are younger and most likely hold advanced practice nursing positions; PhDs are 10 years older and more likely hold administrative or leadership positions. Little evidence exists that neither nurses nor administrators understand the skills and knowledge that doctorally-prepared RNs bring to the organization. This is particularly true for DNPs who predominantly hold clinical positions also held by master's-prepared RNs. Advocates for continued growth of DNPs in academia and practice should partner more closely to clarify the skills and talents that doctorally-prepared nurses bring to clinical settings. Advocates for continued growth of DNPs in academia and practice should partner more closely to clarify the skills and talents that doctorally-prepared nurses bring to clinical settings.In this paper, the local stabilization of memristive neural networks (MNNs) with actuator saturation is investigated via aperiodic sampled-data control. Inspired by the characteristic of the control scheme, a novel sampling-interval-dependent Lyapunov functional (SIDLF) is constructed. The main contribution of the developed Lyapunov functional lies in that the requirement on its positive definiteness is replaced by a looped condition. Then, using some inequality techniques and the discrete-time Lyapunov approach, two sufficient criteria are derived to ensure the local