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Objective: Creating an intracortical brain-computer interface (iBCI) capable of seamless transitions between tasks and contexts would greatly enhance user experience. However, the nonlinearity in neural activity presents challenges to computing a global iBCI decoder. We aimed to develop a method that differs from a globally optimized decoder to address this issue.

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Decomposition-based multi-objective evolutionary algorithms (MOEAs) are popular methods utilized to address many-objective optimization problems (MaOPs). These algorithms decompose the original MaOP into several scalar optimization subproblems, and solve them to obtain a set of solutions to approximate the Pareto front (PF). The decomposition approach is an important component in them.

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Background: Robotic-assisted total knee arthroplasty (RA-TKA) was introduced to provide surgeons with virtual preoperative planning and intraoperative information to achieve the desired surgical goals in an effort to improve patient outcomes. The purpose of this study was to compare clinical outcomes and patient-reported outcome measures following primary TKA using RA-TKA vs manual instrumentation.

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Objectives: To identify the risk factors for postoperative relapse of chronic rhinosinusitis with nasal polyps (CRSwNP) using multivariate Logistic regression analysis and to explore potential improvements in clinical treatment measures.

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Objective: A nanometer-sized vesicles originating from bone marrow mesenchymal stem cells (BMMSCs), called exosomes, have been extensively recognized. This study defines the impact of BMMSCs and their derived exosomes on proliferation, apoptosis and oxidative stress (OS) levels of CP-induced parotid salivary gland damage.

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