No abstract

A plethora of software suites and multiple classes of spectral libraries have been developed to enhance the depth and robustness of data-independent acquisition (DIA) data processing. However, how the combination of a DIA software tool and a spectral library impacts the outcome of DIA proteomics and phosphoproteomics data analysis has been rarely investigated using benchmark data that mimics biological complexity. In this study, we create DIA benchmark data sets simulating the regulation of thousands of proteins in a complex background, which are collected on both an Orbitrap and a timsTOF instruments. We evaluate four commonly used software suites (DIA-NN, Spectronaut, MaxDIA and Skyline) combined with seven different spectral libraries in global proteome analysis. Moreover, we assess their performances in analyzing phosphopeptide standards and TNF-α-induced phosphoproteome regulation. Our study provides a practical guidance on how to construct a robust data analysis pipeline for different proteomics studies implementing the DIA technique.

This paper presents a new electricity power generation architecture for the engine system of more electric aircraft (MEA). A starter/generator (SG) is connected to highpressure (HP) spool, and a generator is attached to low-pressure (LP) spool. Their outputs supply a common DC bus. A back-toback (B2B) converter is connected between the AC sides of two generators. There are two main contributions of the proposed idea. First, some power can be transferred from LP shaft to HP shaft via the B2B converter, which will benefit to reduce the fuel consumption and increase compressor surge margin of the engine. Second, the HP starter/generator could operate in a high speed without flux weakening, hence the magnitude of stator current will largely decrease when output same active power, leading to the reduction of overall power losses. Modeling and control method design are illustrated. The effectiveness of proposed power generation architecture, engine performance improvement and power loss reduction are verified.

Conventional finite control set model predictive control (FCS-MPC) presents high computational burden especially in three-level neutral point clamped (NPC) converters. This paper proposes a low-complexity optimal switching time modulated model predictive control (OST-M2PC) method for three-level NPC converter. In the proposed OST-M2PC method, the optimal switching time is calculated using a cost function. Compared to conventional FCS-MPC, the proposed OST-M2PC method has a fixed switching frequency as well as better power quality. The proposed OST-M2PC can operate at a 20kHz sampling frequency, reducing the computational burden of the processor. Simulation and experimental results validate the operation of the proposed method. Index Terms-Finite control set model predictive control (FCS-MPC), modulated model predictive control (M2PC), permanent magnet synchronous motor (PMSM), optimal switching time modulated model predictive control (OST-M2PC).