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Data‐independent acquisition‐based SWATH‐MS for quantitative proteomics: a tutorial
Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH‐MS is a specific variant of data‐independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH‐MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH‐MS data, a strategy based on peptide‐centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH‐MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH‐MS data using peptide‐centric scoring. Furthermore, concepts on how to improve SWATH‐MS data acquisition, potential trade‐offs of parameter settings and alternative data analysis strategies are discussed.
Graphical Abstract
SWATH‐MS combines deep proteome coverage with quantitative consistency and accuracy and is often the method of choice for personalized medicine, drug screens or systems biology. This tutorial provides guidelines on how to set up SWATH‐MS experiments, perform the mass spectrometric measurements and analyse the data.
Journal Article
Data-driven learning for the next generation : corpora and DDL for pre-tertiary learners
\"Despite advancements in and availability of corpus software in language classrooms facilitating data-driven learning (DDL), the use of such methods with pre-tertiary learners remains rare. This book explores the affordances of DDL specifically for younger learners, testing its viability with teachers and students at the primary and secondary years of schooling. It features eminent and up-and-coming researchers from Europe, Asia, and Australasia who seek to address best practice in implementing DDL with younger learners, while providing a wealth of empirical findings and practical DDL activities ready for use in the pre-tertiary classroom. Divided into three parts, the volume's first section focuses on overcoming emerging challenges for DDL with younger learners, including where and how DDL can be integrated into pre-tertiary curricula, as well as potential barriers to this integration. It then considers new, cutting-edge innovations in corpora and corpus software for use with younger learners in the second section, before reporting on actual DDL studies performed with younger learners (and their teachers) at the primary and secondary levels of education. This book will appeal to post-graduate students, academics and researchers with interests in corpus linguistics, second language acquisition, primary and secondary literacy education, and language and educational technologies\"-- Provided by publisher.
Book
Wind turbine icing characteristics and icing-induced power losses to utility-scale wind turbines
A field campaign was carried out to investigate ice accretion features on large turbine blades (50 m in length) and to assess power output losses of utility-scale wind turbines induced by ice accretion. After a 30-h icing incident, a high-resolution digital camera carried by an unmanned aircraft system was used to capture photographs of iced turbine blades. Based on the obtained pictures of the frozen blades, the ice layer thickness accreted along the blades’ leading edges was determined quantitatively. While ice was found to accumulate over whole blade spans, outboard blades had more ice structures, with ice layers reaching up to 0.3 m thick toward the blade tips. With the turbine operating data provided by the turbines’ supervisory control and data acquisition systems, icing-induced power output losses were investigated systematically. Despite the high wind, frozen turbines were discovered to rotate substantially slower and even shut down from time to time, resulting in up to 80% of icing-induced turbine power losses during the icing event. The research presented here is a comprehensive field campaign to characterize ice accretion features on full-scaled turbine blades and systematically analyze detrimental impacts of ice accumulation on the power generation of utility-scale wind turbines. The research findings are very useful in bridging the gaps between fundamental icing physics research carried out in highly idealized laboratory settings and the realistic icing phenomena observed on utility-scale wind turbines operating in harsh natural icing conditions.
Journal Article
Ultra-Low-Power Sensor Nodes for Real-Time Synchronous and High-Accuracy Timing Wireless Data Acquisition
This paper presents an energy-efficient and high-accuracy sampling synchronization approach for real-time synchronous data acquisition in wireless sensor networks (saWSNs). A proprietary protocol based on time-division multiple access (TDMA) and deep energy-efficient coding in sensor firmware is proposed. A real saWSN model based on 2.4 GHz nRF52832 system-on-chip (SoC) sensors was designed and experimentally tested. The obtained results confirmed significant improvements in data synchronization accuracy (even by several times) and power consumption (even by a hundred times) compared to other recently reported studies. The results demonstrated a sampling synchronization accuracy of 0.8 μs and ultra-low power consumption of 15 μW per 1 kb/s throughput for data. The protocol was well designed, stable, and importantly, lightweight. The complexity and computational performance of the proposed scheme were small. The CPU load for the proposed solution was <2% for a sampling event handler below 200 Hz. Furthermore, the transmission reliability was high with a packet error rate (PER) not exceeding 0.18% for TXPWR ≥ −4 dBm and 0.03% for TXPWR ≥ 3 dBm. The efficiency of the proposed protocol was compared with other solutions presented in the manuscript. While the number of new proposals is large, the technical advantage of our solution is significant.
Journal Article
Low-cost technologies used in corrosion monitoring
Globally, corrosion is the costliest cause of the deterioration of metallic and concrete structures, leading to significant financial losses and unexpected loss of life. Therefore, corrosion monitoring is vital to the assessment of structures’ residual performance and for the identification of pathologies in early stages for the predictive maintenance of facilities. However, the high price tag on available corrosion monitoring systems leads to their exclusive use for structural health monitoring applications, especially for atmospheric corrosion detection in civil structures. In this paper a systematic literature review is provided on the state-of-the-art electrochemical methods and physical methods used so far for corrosion monitoring compatible with low-cost sensors and data acquisition devices for metallic and concrete structures. In addition, special attention is paid to the use of these devices for corrosion monitoring and detection for in situ applications in different industries. This analysis demonstrates the possible applications of low-cost sensors in the corrosion monitoring sector. In addition, this study provides scholars with preferred techniques and the most common microcontrollers, such as Arduino, to overcome the corrosion monitoring difficulties in the construction industry.
Journal Article
Design and implementation of a multi-channel data acquisition system based on STM32 and Qt
To meet the requirements of high precision, multi-channel capability, and real-time performance for data acquisition in scientific research, industrial production, and other fields, a multi-channel data acquisition system based on the STM32 microcontroller and Qt development framework is designed and implemented. The system adopts the STM32F407ZGT6 as the main control chip of the lower computer, collects multi-channel environmental data through temperature, humidity, illuminance, and noise sensors, and transmits the data to the upper computer via serial communication after digital filtering and preprocessing. The upper computer is developed based on Qt 5.9.1, integrating functions such as real-time data display, curve plotting, MySQL database storage, and historical data query. Test results indicate that the system features a stable sampling rate, reliable data transmission, and a measurement error of less than ±1%. It can realize synchronous acquisition, real-time monitoring, and offline analysis of 4-channel sensor signals, satisfying the needs of data acquisition applications in various scenarios.
Journal Article
Non-target data acquisition for target analysis (nDATA) of 845 pesticide residues in fruits and vegetables using UHPLC/ESI Q-Orbitrap
A non-target data acquisition for target analysis (nDATA) workflow based on accurate mass measurements using UHPLC/ESI Q-Orbitrap full MS-data-independent acquisition and a compound database was developed to screen pesticide residues in fruit and vegetable samples. The compound database of 845 pesticides was built from dd-MS2 (data-dependent acquisition) product ion spectral data and LC retention times of individual pesticide standards. MS2 spectra of samples were acquired using multiplexing data-independent acquisition (mDIA) and variable data-independent acquisition (vDIA). Screening of pesticides in samples was based on either the retention time (± 0.5 min) and the mass accuracy (± 5 ppm) of a precursor (RTP by full MS) or the retention time (± 0.5 min) and the mass accuracy (± 5 ppm) of a precursor and its fragment ion (RTFI by full MS/DIA). In validation studies involving mDIA and vDIA analysis of 10 fruits and vegetables spiked with pesticides prior to QuEChERS sample preparation, RTP correctly found up to 765 and 796 pesticides at 10 and 100 μg/kg, respectively, whereas RTFI correctly identified up to 729 and 764 pesticides at the same respective concentrations. UHPLC/ESI Q-Orbitrap full MS/mDIA or vDIA proved to be a comprehensive detection technique and has potential for pesticide residue screening in fruits and vegetables.
Journal Article
A Low-Cost Multi-Sensor Data Acquisition System for Fault Detection in Fused Deposition Modelling
Fused deposition modelling (FDM)-based 3D printing is a trending technology in the era of Industry 4.0 that manufactures products in layer-by-layer form. It shows remarkable benefits such as rapid prototyping, cost-effectiveness, flexibility, and a sustainable manufacturing approach. Along with such advantages, a few defects occur in FDM products during the printing stage. Diagnosing defects occurring during 3D printing is a challenging task. Proper data acquisition and monitoring systems need to be developed for effective fault diagnosis. In this paper, the authors proposed a low-cost multi-sensor data acquisition system (DAQ) for detecting various faults in 3D printed products. The data acquisition system was developed using an Arduino micro-controller that collects real-time multi-sensor signals using vibration, current, and sound sensors. The different types of fault conditions are referred to introduce various defects in 3D products to analyze the effect of the fault conditions on the captured sensor data. Time and frequency domain analyses were performed on captured data to create feature vectors by selecting the chi-square method, and the most significant features were selected to train the CNN model. The K-means cluster algorithm was used for data clustering purposes, and the bell curve or normal distribution curve was used to define individual sensor threshold values under normal conditions. The CNN model was used to classify the normal and fault condition data, which gave an accuracy of around 94%, by evaluating the model performance based on recall, precision, and F1 score.
Journal Article
GuPPy, a Python toolbox for the analysis of fiber photometry data
Fiber photometry (FP) is an adaptable method for recording in vivo neural activity in freely behaving animals. It has become a popular tool in neuroscience due to its ease of use, low cost, the ability to combine FP with freely moving behavior, among other advantages. However, analysis of FP data can be challenging for new users, especially those with a limited programming background. Here, we present Guided Photometry Analysis in Python (GuPPy), a free and open-source FP analysis tool. GuPPy is designed to operate across computing platforms and can accept data from a variety of FP data acquisition systems. The program presents users with a set of graphic user interfaces (GUIs) to load data and provide input parameters. Graphs are produced that can be easily exported for integration into scientific figures. As an open-source tool, GuPPy can be modified by users with knowledge of Python to fit their specific needs.
Journal Article