The development of a meta-learning calibration network for low-cost sensors across domains

Low-cost sensor arrays are an economical and efficient solution for large-scale networked monitoring of atmospheric pollutants. These sensors need to be calibrated in situ before use, and existing data-driven calibration models have been widely used, but require large amounts of co-location data with reference stations for training, while performing poorly across domains. To address this problem, a meta-learningbased calibration network for air sensors is proposed, which has been tested on ozone datasets. The tests have proved that it outperforms five other conventional methods in important metrics such as mean absolute error, root mean square error and correlation coefficient. Taking Manlleu and Tona as the source domain and Vic as the target domain, the proposed method reduces MAE and RMSE by 17.06% and 6.71% on average, and improves R2 by an average of 4.21%, compared with the suboptimal pre-trained multi-source transfer calibration. The method can provide a new idea and direction to solve the problem of cross-domain and reliance on a large amount of co-location data in the calibration of sensors

vim: Research on OWL-Based Vocabulary Ontology Construction Method for Units of Measurement

The advent of the digital era has put forward an urgent demand for the digitization of units of measurement, and the construction of unit ontology is an important method to realize the digitization of units of measurement. However, the existing unit ontology is at the preliminary research stage, especially the bilingual unit of measurement suitable for the construction of Digital China. Based on the Web Ontology Language (OWL), a bilingual unit of measurement ontology, vim, is designed and constructed using the Seven Steps to Ontology Development approach. vim provides a standardized, interoperable, and unified architecture to realize the bilingual digital representation of units in the International Vocabulary of Metrology—Basic and general concepts (VIM) and from the Chinese metrological technical specification JJF 1001-2011 General Terms in Metrology and Their Definitions. The ontology was verified for machine readability, knowledge reasoning capability, and semantic retrieval and applied. The experimental results show that the vim ontology can achieve machine readability with correct syntax, logical consistency, and validity, and can facilitate data communication and sharing. Furthermore, a comparison between vim, OM, and QUDT was conducted. OM and QUDT serve as representative instances in the field of ontology for units. The construction of this ontology lays the foundation for realizing the digitization and standardization of China’s unit of measurement, as well as the machine-readability, interoperability, and sharing of domestic and foreign metrology test data and metrology certificates

Progressive Feature Reconstruction and Fusion to Accelerate MRI Imaging: Exploring Insights across Low, Mid, and High-Order Dimensions

Magnetic resonance imaging (MRI) faces ongoing challenges associated with prolonged acquisition times and susceptibility to motion artifacts. Compressed Sensing (CS) principles have emerged as a significant advancement, addressing these issues by subsampling k-space data points and enabling rapid imaging. Nevertheless, the recovery of intricate details from under-sampled data remains a complex endeavor. In this study, we introduce an innovative deep learning approach tailored to the restoration of high-fidelity MRI images from under-sampled k-space data. Our method employs a cascaded reconstruction strategy that progressively restores hierarchical features and fuses them to achieve the final reconstruction. This cascade encompasses low, intermediate, and high orders of reconstruction, which is followed by a return through intermediate and low orders. At distinct reconstruction stages, we introduce a novel reconstruction block to recapture diverse frequency information crucial for image reconstruction. The other core innovation of our proposal lies in a fusion algorithm that harmonizes results from various reconstruction tiers into the final MRI image. Our methodology is validated using two distinct datasets. Notably, our algorithm achieves impressive PSNR values of 32.60 and 31.02 at acceleration factors of 4× and 8× in the FastMRI dataset along with SSIM scores of 0.818 and 0.771, outperforming current state-of-the-art algorithms. Similarly, on the Calgary–Campinas dataset, our algorithm achieves even higher PSNR values, reaching 37.68 and 33.44, which is accompanied by substantial SSIM scores of 0.954 and 0.901. It is essential to highlight that our algorithm achieves these remarkable results with a relatively lower parameter count, underscoring its efficiency. Comparative analyses against analogous methods further emphasize the superior performance of our approach, providing robust evidence of its effectiveness

Boosting the Signal Intensity of Nanoelectrospray Ionization by Using a Polarity-Reversing High-Voltage Strategy

Continuous efforts have been made to further improve the performance of nano-ESI. In this work, we made use of a polarity-reversing high-voltage strategy for the generation of nano-ESI (PR-nESI). Typically, a negative high voltage of −3.0 kV was first applied to the electrode and maintained for 6 s. Then the polarity was reversed, and a positive high voltage of +1.75 kV was applied for the generation of electrospray. Compared with conventional nano-ESI, PR-nESI significantly enhanced the signal intensity of protonated protein ions. The signal-to-noise ratio (S/N) of protonated protein ions was increased by 1–2 orders of magnitude. The increase of S/N was even more remarkable at lower concentrations. Furthermore, PR-nESI also had a desalting effect. Metal ion adducts of proteins were effectively removed. No metal ion adducts were identified from the spectra, even if the concentration of salt was increased to the millimolar level. The performance of PR-nESI was confirmed in the detection of different molecules including proteins, peptides, amino acids, and other small-molecule compounds. The intact folded structure of proteins was preserved during PR-nESI. No unfolding was observed in the spectra. PR-nESI was further applied to the analysis of noncovalent protein–ligand complexes and protein digest. At last, investigations into the mechanism of PR-nESI were carried out. The enhancement of signal intensity and desalting effect were related to the electromigration of the solutes in solution. With all the advantages above, PR-nESI would be a promising method in the future analytical and bioanalytical applications

Detecting Low-Abundance Molecules at Single-Cell Level by Repeated Ion Accumulation in Ion Trap Mass Spectrometer

Low-abundance metabolites or proteins in single-cell samples are usually undetectable by mass spectrometry (MS) due to the limited amount of substances in single cells. This limitation inspired us to further enhance the sensitivity of commercial mass spectrometers. Herein, we developed a technique named repeated ion accumulation by ion trap MS, which is capable of enhancing the sensitivity by selectively and repeatedly accumulating ions in a linear ion trap for up to 25 cycles. The increase in MS sensitivity was positively correlated with the number of repeated cycles. When ions were repeatedly accumulated for 25 cycles, the sensitivity of adenosine triphosphate detection was increased by 22-fold within 1.8 s. Our technique could stably detect low-abundance ions, especially MS<i>ⁿ</i> ions, at the single-cell level, such as 5-methylcytosine hydrolyzed from sample equivalent to ∼0.2 MCF7 cell. The strategy presented in this study offers the possibility to aid single-cell analysis by enhancing MS detection sensitivity

Detecting Low-Abundance Molecules at Single-Cell Level by Repeated Ion Accumulation in Ion Trap Mass Spectrometer

Low-abundance metabolites or proteins in single-cell samples are usually undetectable by mass spectrometry (MS) due to the limited amount of substances in single cells. This limitation inspired us to further enhance the sensitivity of commercial mass spectrometers. Herein, we developed a technique named repeated ion accumulation by ion trap MS, which is capable of enhancing the sensitivity by selectively and repeatedly accumulating ions in a linear ion trap for up to 25 cycles. The increase in MS sensitivity was positively correlated with the number of repeated cycles. When ions were repeatedly accumulated for 25 cycles, the sensitivity of adenosine triphosphate detection was increased by 22-fold within 1.8 s. Our technique could stably detect low-abundance ions, especially MS<i>ⁿ</i> ions, at the single-cell level, such as 5-methylcytosine hydrolyzed from sample equivalent to ∼0.2 MCF7 cell. The strategy presented in this study offers the possibility to aid single-cell analysis by enhancing MS detection sensitivity

Ambient Mass Spectrometry Imaging: Plasma Assisted Laser Desorption Ionization Mass Spectrometry Imaging and Its Applications

Mass spectrometry imaging (MSI) has been widely used in many research areas for the advantages of providing informative molecular distribution with high specificity. Among the recent progress, ambient MSI has attracted increasing interests owing to its characteristics of ambient, in situ, and nonpretreatment analysis. Here, we are presenting the ambient MSI for traditional Chinese medicines (TCMs) and authentication of work of art and documents using plasma assisted laser desorption ionization mass spectrometry (PALDI-MS). Compared with current ambient MSI methods, an excellent average resolution of 60 mu m x 60 mu m pixel size was achieved using this system. The feasibility of PALDI-based MSI was confirmed by seal imaging, and its authentication applications were demonstrated by imaging of printed Chinese characters. Imaging of the Radix Scutellariae slice showed that the two active components, baicalein and wogonin, mainly were distributed in the epidermis of the root, which proposed an approach for distinguishing TCMs' origins and the distribution of active components of TCMs and exploring the environmental effects of plant growth. PALDI-MS imaging provides a strong complement for the MSI strategy with the enhanced spatial resolution, which is promising in many research fields, such as artwork identification, TCMs' and botanic research, pharmaceutical applications, etc

Elucidating the various multi-phosphorylation statuses of protein functional regions by 193-nm ultraviolet photodissociation

The 193-nm ultraviolet photodissociation strategy could significantly improve the MS ability in elucidating the confused phosphorylation sites with multiple possible positions due to its ability in generating more phosphorylation site-determining ions and providing higher sequence coverage

Elucidating the various multi-phosphorylation statuses of protein functional regions by 193-nm ultraviolet photodissociation

The 193-nm ultraviolet photodissociation strategy could significantly improve the MS ability in elucidating the confused phosphorylation sites with multiple possible positions due to its ability in generating more phosphorylation site-determining ions and providing higher sequence coverage