Reducing Measurement Costs of Thermal Power: An Advanced MISM (Mamba with Improved SSM Embedding in MLP) Regression Model for Accurate CO2 Emission Accounting.

Current calculation methods for the carbon content as received (Car) of coal rely on multiple instruments, leading to high costs for enterprises. There is a need for a cost-effective model that maintains accuracy in CO2 emission accounting. This study introduces an MISM model using key parameters identified through correlation and ablation analyses. An Improved State-Space Model (ISSM) and an IS-Mamba module are integrated into a Multi-Layer Perceptron (MLP) framework, enhancing information flow and regression accuracy. The MISM model demonstrates superior performance over traditional methods, reducing the Root Mean Square Error (RMSE) by 22.36% compared to MLP, and by 9.65% compared to Mamba. Using only six selected parameters, the MISM model achieves a precision of 0.27% for the discrepancy between the calculated CO2 emissions and the actual measurements. An ablation analysis confirms the importance of certain parameters and the effectiveness of the IS-Mamba module at improving model performance. This paper offers an innovative solution for accurate and cost-effective carbon accounting in the thermal power sector, supporting China's carbon peaking and carbon neutrality goals.

Design and Implementation of Digital Calibration Certificate for RFID Tag Storage.

The digital transformation of metrology is one of the most active activities in the field of metrology at present, where the digital calibration certificate (DCC) being developed is the topic receiving the most concern in the current digital transformation. In practical industrial applications, the issue of storage carrier for the DCC plays a crucial role in its promotion and implementation. To address this issue, a DCC meta-model called DCC-Lite schema has been designed along with a corresponding processing method. This solution involves compressing and segmenting the DCC to make it suitable for storage using RFID tags. These RFID tags are affixed to the instruments and accompany them throughout their usage. Additionally, the DCC-RFID processing system has been developed to validate the effectiveness of the DCC meta-model and its corresponding processing method within a wireless temperature acquisition system. Experimental results demonstrate that the system successfully reads and writes the DCC stored within the RFID tag group. Furthermore, it enables automated parsing of the DCC calibration data by the machine and real-time compensation of measurement data to reduce measurement errors.

MSA-Net: A Precise and Robust Model for Predicting the Carbon Content on an As-Received Basis of Coal.

The carbon content as received (Car) of coal is essential for the emission factor method in IPCC methodology. The traditional carbon measurement mechanism relies on detection equipment, resulting in significant detection costs. To reduce detection costs and provide precise predictions of Cars even in the absence of measurements, this paper proposes a neural network combining MLP with an attention mechanism (MSA-Net). In this model, the Attention Module is proposed to extract important and potential features. The Skip-Connections are utilized for feature reuse. The Huber loss is used to reduce the error between predicted Car values and actual values. The experimental results show that when the input includes eight measured parameters, the MAPE of MSA-Net is only 0.83%, which is better than the state-of-the-art Gaussian Process Regression (GPR) method. MSA-Net exhibits better predictive performance compared to MLP, RNN, LSTM, and Transformer. Moreover, this article provides two measurement solutions for thermal power enterprises to reduce detection costs.

Design and Implementation of an Ontology for Measurement Terminology in Digital Calibration Certificates.

Digital Calibration Certificates (DCCs) are a key focus in metrology digitalization, necessitating that they satisfy the criteria for machine readability and understandability. Current DCCs are machine-readable, but they are still missing the essential semantic information required for machine understandability. This shortfall is particularly notable in the lack of a dedicated semantic ontology for measurement terminologies. This paper proposes a domain ontology for measurement terminologies named the OMT (Ontology for Measurement Terminology), using a foundation of metrological terms from standards like the International Vocabulary of Metrology (VIM), the Guide to the Expression of Uncertainty in Measurement (GUM), and JJF1001. It also incorporates insights from models such as the SI Reference Point, the Simple Knowledge Organization System (SKOS), and the DCC Schema. The methodology was guided by Stanford's Seven-Step Method, ensuring a systematic development process tailored to the needs of metrological semantics. Through semantic expression capability verification and SPARQL query validations, the OMT has been confirmed to possess essential machine readability and understandability features. It has been successfully integrated into version 3.2.1 of DCCs across ten representative domains. This integration demonstrates an effective method for ensuring that DCCs are machine-readable and capable of interoperating within digital environments, thereby advancing the research in metrology digitization.

Generating Supercharged Protein Ions for Breath Analysis by Extractive Electrospray Ionization Mass Spectrometry.

Supercharged protein ions produced by electrospray ionization are extremely efficient proton donors for secondary ionization. Here, by electrospraying the protein solutions containing 5% 1,2-butylene carbonate, the supercharged protein ions with unusually high proton density were produced as the primary ions for the ionization of exhaled breath samples in the extractive electrospray ionization mass spectrometry (EESI-MS), which resulted in the enhanced ionization efficiency for the breath analytes even with relatively low gas phase basicity. Moreover, the total number of metabolites detected in breath increased by about 260% in the mass range of 200-500 Da, owing to the substantial signal enhancement for breath metabolites, providing complementary and additional information to conventional SESI.

Atg20- and Atg24-family proteins promote organelle autophagy in fission yeast.

Autophagy cargos include not only soluble cytosolic materials but also bulky organelles, such as ER and mitochondria. In budding yeast, two proteins that contain the PX domain and the BAR domain, Atg20 and Atg24 (also known as Snx42 and Snx4, respectively) are required for organelle autophagy and contribute to general autophagy in a way that can be masked by compensatory mechanisms. It remains unclear why these proteins are important for organelle autophagy. Here, we show that in a distantly related fungal organism, the fission yeast Schizosaccharomyces pombe, autophagy of ER and mitochondria is induced by nitrogen starvation and is promoted by three Atg20- and Atg24-family proteins - Atg20, Atg24 and SPBC1711.11 (named here as Atg24b). These proteins localize at the pre-autophagosomal structure, or phagophore assembly site (PAS), during starvation. S. pombe Atg24 forms a homo-oligomer and acts redundantly with Atg20 and Atg24b, and the latter two proteins can form a hetero-oligomer. The organelle autophagy defect caused by the loss of these proteins is associated with a reduction of autophagosome size and a decrease in Atg8 accumulation at the PAS. These results provide new insights into the autophagic function of Atg20- and Atg24-family proteins.

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 MSn 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.

Desalting by crystallization: detection of attomole biomolecules in picoliter buffers by mass spectrometry.

Sensitive detection of biomolecules in small-volume samples by mass spectrometry is, in many cases, challenging because of the use of buffers to maintain the biological activities of proteins and cells. Here, we report a highly effective desalting method for picoliter samples. It was based on the spontaneous separation of biomolecules from salts during crystallization of the salts. After desalting, the biomolecules were deposited in the tip of the quartz pipet because of the evaporation of the solvent. Subsequent detection of the separated biomolecules was achieved using solvent assisted electric field induced desorption/ionization (SAEFIDI) coupled with mass spectrometry. It allowed for direct desorption/ionization of the biomolecules in situ from the tip of the pipet. The organic component in the assistant solvent inhibited the desorption/ionization of salts, thus assured successful detection of biomolecules. Proteins and peptides down to 50 amol were successfully detected using our method even if there were 3 × 10(5) folds more amount of salts in the sample. The concentration and ion species of the salts had little influence on the detection results.

Pulsed Direct Current Electrospray: Enabling Systematic Analysis of Small Volume Sample by Boosting Sample Economy.

We had developed pulsed direct current electrospray ionization mass spectrometry (pulsed-dc-ESI-MS) for systematically profiling and determining components in small volume sample. Pulsed-dc-ESI utilized constant high voltage to induce the generation of single polarity pulsed electrospray remotely. This method had significantly boosted the sample economy, so as to obtain several minutes MS signal duration from merely picoliter volume sample. The elongated MS signal duration enable us to collect abundant MS(2) information on interested components in a small volume sample for systematical analysis. This method had been successfully applied for single cell metabolomics analysis. We had obtained 2-D profile of metabolites (including exact mass and MS(2) data) from single plant and mammalian cell, concerning 1034 components and 656 components for Allium cepa and HeLa cells, respectively. Further identification had found 162 compounds and 28 different modification groups of 141 saccharides in a single Allium cepa cell, indicating pulsed-dc-ESI a powerful tool for small volume sample systematical analysis.

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 µm × 60 µm 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.

Ion collision crosssection measurements in quadrupole ion traps using a time-frequency analysis method.

In this study, a method for measuring ion collision crosssections (CCSs) was proposed through time-frequency analysis of ion trajectories in quadrupole ion traps. A linear ion trap with added high-order electric fields was designed and simulated. With the presence of high-order electric fields and ion-neutral collisions, ion secular motion frequency within the quadrupole ion trap will be a function of ion motion amplitude, thus a function of time and ion CCS. A direct relationship was then established between ion CCS and ion motion frequency with respect to time, which could be obtained through time-frequency analysis of ion trajectories (or ion motion induced image currents). To confirm the proposed theory, realistic ion trajectory simulations were performed, where the CCSs of bradykinin, angiotensin I and II, and ubiquitin ions were calculated from simulated ion trajectories. As an example, differentiation of isomeric ubiquitin ions was also demonstrated in the simulations.

CRNN-Refined Spatiotemporal Transformer for Dynamic MRI reconstruction.

Magnetic Resonance Imaging (MRI) plays a pivotal role in modern clinical practice, providing detailed anatomical visualization with exceptional spatial resolution and soft tissue contrast. Dynamic MRI, aiming to capture both spatial and temporal characteristics, faces challenges related to prolonged acquisition times and susceptibility to motion artifacts. Balancing spatial and temporal resolutions becomes crucial in real-world clinical scenarios. In the realm of dynamic MRI reconstruction, while Convolutional Recurrent Neural Networks (CRNNs) struggle with long-range dependencies, CRNNs require extensive iterations, impacting efficiency. Transformers, known for their effectiveness in high-dimensional imaging, are underexplored in dynamic MRI reconstruction. Additionally, prevailing algorithms fall short of achieving superior results in demanding generative reconstructions at high acceleration rates. This research proposes a novel approach for dynamic MRI reconstruction, named CRNN-Refined Spatiotemporal Transformer Network (CST-Net). The spatiotemporal Transformer initiates reconstruction, modeling temporal and spatial correlations, followed by refinement using the CRNN. This integration mitigates inaccuracies caused by damaged frames and reduces CRNN iterations, enhancing computational efficiency without compromising reconstruction quality. Our study compares the performance of the proposed CST-Net at 6 × and 12 × undersampling rates, showcasing its superiority over existing algorithms. Particularly, in challenging 25× generative reconstructions, the CST-Net outperforms current methods. The comparison includes experiments under both radial and Cartesian undersampling patterns. In conclusion, CST-Net successfully addresses the limitations inherent in existing generative reconstruction algorithms, thereby paving the way for further exploration and optimization of Transformer-based approaches in dynamic MRI reconstruction. Code and Datasets can be available: https://github.com/XWangBin/CST-Net.

DCT-net: Dual-domain cross-fusion transformer network for MRI reconstruction.

Current challenges in Magnetic Resonance Imaging (MRI) include long acquisition times and motion artifacts. To address these issues, under-sampled k-space acquisition has gained popularity as a fast imaging method. However, recovering fine details from under-sampled data remains challenging. In this study, we introduce a pioneering deep learning approach, namely DCT-Net, designed for dual-domain MRI reconstruction. DCT-Net seamlessly integrates information from the image domain (IRM) and frequency domain (FRM), utilizing a novel Cross Attention Block (CAB) and Fusion Attention Block (FAB). These innovative blocks enable precise feature extraction and adaptive fusion across both domains, resulting in a significant enhancement of the reconstructed image quality. The adaptive interaction and fusion mechanisms of CAB and FAB contribute to the method's effectiveness in capturing distinctive features and optimizing image reconstruction. Comprehensive ablation studies have been conducted to assess the contributions of these modules to reconstruction quality and accuracy. Experimental results on the FastMRI (2023) and Calgary-Campinas datasets (2021) demonstrate the superiority of our MRI reconstruction framework over other typical methods (most are illustrated in 2023 or 2022) in both qualitative and quantitative evaluations. This holds for knee and brain datasets under 4× and 8× accelerated imaging scenarios.

Non-contact halogen lamp heating assisted LTP ionization miniature rectilinear ion trap: a platform for rapid, on-site explosives analysis.

A platform consisting of a halogen lamp, a low temperature plasma (LTP) probe, and a miniature rectilinear ion trap mass spectrometer (RIT-MS) has been constructed and evaluated to detect organic and inorganic explosives on solid surfaces. This platform features two attractive characteristics: high sensitivity for the explosives with low volatility, and rapid analysis speed for the explosives on large surface areas. With non-contact heating by the halogen lamp, the signal intensities for the explosives with relatively high volatility were improved by over an order of magnitude, compared to those obtained at room temperature; and even more, the explosives with low volatility, which could hardly be detected at room temperature, were able to be readily identified. The limits of detection (LODs) of the selected explosives were all at the picogram level (e.g., 10 pg and 20 pg for TNT and RDX, respectively) with a heating time of 3 s. Using manual surface swabbing, the analysis of explosives on a large surface area (7.5 cm × 2.5 cm) was accomplished within 10 s, and an acceptable sensitivity could be acquired; additionally, inorganic explosives (black powder and firecracker) were successfully detected. Without any sample pretreatment, the platform was used to analyze the wastewater from an explosives factory, confirming the existence of 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (2,4-DNT), and 2,6-dinitrotoluene (2,6-DNT), and the concentration of TNT was determined to be 5 ng mL(-1). All these results indicated that the proposed platform was a promising technique for security monitoring and environmental analysis.

Enhanced Desorption Electrospray Ionization Mass Spectrometry via Synchronizing Ion Generation and Ion Injection.

A modified version of desorption electrospray ionization mass spectrometry was developed for (i) better utilization of analyte ions and (ii) larger sampling area via synchronization the pulsed nebulizer gas with ion injection. To synchronize the sheath gas, gas flow was paused for 50 ms within each cycle, leading to solvent accumulation at the end of emitter tip. That solvent accumulation enlarged the desorption areas. As a result, the amount of analytes increased. Thus, the improved signal intensity (~ 2-5-folds for various substrates) was benefit from both better analyte ion utilization and larger desorption areas. Finally, the enhanced signal intensity was confirmed with both garlic homogenate and brain homogenate. Graphical Abstract ᅟ.

[Determination of seven indicative ingredients in oral liquids of Chinese medicine by liquid chromatography-electrospray ionization-ion mobility spectrometry].

A two-dimensional separation and analysis method, based on liquid chromatography-electrospray ionization-ion mobility spectrometry (LC-ESI-IMS), is developed for the determination of seven indicative ingredients (danshensu, glycyrrhizic acid, gastrodin, chlorogenic acid, puerarin, baicalin, and rutin) in oral liquids of Chinese medicine. The sample was first separated on an ACQUITY UPLC BEH C18 column (50 mm×1 mm, 1.7 µm). The post-column effluent was directed to an adjustable flow splitter with a split ratio of 50:1. The low-flow and high-flow outlets were connected to an ion mobility spectrometer and a triple quadrupole mass spectrometer, respectively. The experimental conditions for LC, spray voltage, drift tube temperature, gas pre-heating temperature, and drift gas velocity were systematically optimized. The limits of detection (LODs) and quantitation (LOQs) for the seven analytes were 2-10 µg/mL and 5-25 µg/mL, respectively. The proposed method was applied for the analysis of real oral liquids of Chinese medicine samples. By coupling LC and IMS, two-dimensional separation could be achieved based on hydrophobicity difference and ionic mobility disparity, thus providing more comprehensive measurement information than LC or IMS used alone.

Ion manipulation and enrichment mass spectrometer for cleavage of disulfide bond via ion/ion reaction.

A novel mass spectrometer with the capability of ion manipulation and enrichment was developed to perform gas-phase ion/ion reactions followed by product ions accumulation. The development of this apparatus opens opportunities for more complex sequences of ion manipulations, thus offers the potential on extensive application involving ion/ion reaction. Here, cleavage of disulfide bond in peptide was demonstrated based upon this ion manipulation and enrichment mass spectrometer. Two typical peptides including S-glutathionylated ARACAKA with an intermolecular disulfide bond, and oxytocin with an intramolecular disulfide bond were chosen as typical samples to demonstrate the ability of the apparatus. After ion/ion reaction between selected peptide cations and periodate ions (IO4 - ), two kinds of product ions (eg, [M + O + H]+ and [M + H + Na + IO4 ]+ ) were enriched with a number of accumulation events. Afterwards, the enriched ions were subjected to activation, and the disulfide bond cleavage was clearly observed from the tandem mass spectra. These results illustrate the potential of this apparatus for ion manipulation performing ion/ion reaction, and low abundance product ion enrichment.

Investigating the structural transitions of proteins during dissolution by mass spectrometry.

An appropriate solvent environment is essential for the implementation of biological functions of proteins. Interactions between protein residues and solvent molecules are of great importance for proteins to maintain their active structure and catalyze biochemical reactions. In this study, we investigated such interactions and studied the structural transitions of proteins during their dissolution process. Our previously developed technique, namely solvent assisted electric field induced desorption/ionization, was used for the dissolution and immediate ionization of proteins. Different solvents and proteins were involved in the investigation. According to the results, cytochrome c underwent significant unfolding during dissolution in the most commonly used NH4Ac buffer. The unfolding got more serious when the concentration of NH4Ac was further increased. Extending the dissolution time resulted in the re-folding of cytochrome c. In comparison, no unfolding was observed if cytochrome c was pre-dissolved in NH4Ac buffer and detected by nano-ESI. Furthermore, no unfolding was observed during the dissolution process of cytochrome c in water. Interactions between the residues of cytochrome c and the solute of NH4Ac might be the reason for the unfolding phenomenon. Similar unfolding phenomenon was observed on holo-myoglobin. However, the observed dissolution feature of insulin was different. No unfolding was observed on insulin during dissolution in NH4Ac buffers. Insulin underwent observable unfolding when water was used for dissolution. This might be due to the structural difference between different proteins. The obtained results in the present study furthered our insights into the interactions between proteins and the solvents during the phase transition of dissolution.

Dual-Polarity Ion Trap Mass Spectrometry: Dynamic Monitoring and Controlling Gas-phase Ion-Ion Reactions.

A dual-polarity linear ion trap (LIT) mass spectrometer was developed in this study, and the method for simultaneously controlling and detecting cations and anions was proposed and realized in the LIT. With the application of an additional dipolar DC field on the ejection electrodes of an LIT, dual-polarity mass spectra could be obtained, which include both the mass-to-charge (m/z) ratio and charge polarity information of an ion. Compared with conventional method, the ion ejection and detection efficiency could also be improved by about one-fold. Furthermore, ion-ion reactions within the LIT could be dynamically controlled and monitored by manipulating the distributions of ions with opposite charge polarities. This method was then used to control and study the reaction kinetics of ion-ion reactions, including electron transfer dissociation (ETD) and charge inversion reactions. A dual-polarity collision-induced dissociation (CID) experiment was proposed and performed to enhance the sequence coverage of a peptide ion. Ion trajectory simulations were also carried out for concept validation and system optimization. Graphical Abstract ᅟ.