Research on photovoltaic MPPT under complex conditions based on an advanced great wall construction algorithm method.

To mitigate the challenges posed by the non-linear multi-peak power-voltage output characteristics of photovoltaic (PV) systems operating under partial shading conditions, which often lead to suboptimal performance of conventional Maximum Power Point Tracking (MPPT) algorithms, a novel approach was introduced. We introduce the LGWGCA-P&O method, which synergistically combines an modified Great Wall Construction Algorithm (LGWGCA) with the Perturbation and Observation (P&O) technique. The LGWGCA is refined with a positional update mechanism inspired by the Grey Wolf Optimization (GWO) algorithm, optimizing the distribution of solution agents, while a Levy flight strategy is employed to reduce excessive randomness during agent replacement and recombination, thereby accelerating the tracking process.

Bilateral globus pallidus interna deep brain stimulation in Parkinson's disease: Therapeutic effects and motor outcomes prediction in a short-term follow up.

Objective: We aimed to compare the motor effect of bilateral globus pallidus interna (GPi) deep brain stimulation (DBS) on motor subtypes of Parkinson's disease (PD) patients and identify preoperative predictive factors of short-term motor outcome.

Methods: We retrospectively investigated bilateral GPi DBS clinical outcomes in 55 PD patients in 1 year follow up. Motor outcome was measured by the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III before and 1 year after surgery.