Histone Lactylation Boosts Reparative Gene Activation Post-Myocardial Infarction.

BACKGROUND: Inflammation resolution and cardiac repair initiation after myocardial infarction (MI) require timely activation of reparative signals. Histone lactylation confers macrophage homeostatic gene expression signatures via transcriptional regulation. However, the role of histone lactylation in the repair response post-MI remains unclear. We aimed to investigate whether histone lactylation induces reparative gene expression in monocytes early and remotely post-MI. METHODS: Single-cell transcriptome data indicated that reparative genes were activated early and remotely in bone marrow and circulating monocytes before cardiac recruitment. Western blotting and immunofluorescence staining revealed increases in histone lactylation levels, including the previously identified histone H3K18 lactylation in monocyte-macrophages early post-MI. Through joint CUT&Tag and RNA-sequencing analyses, we identified Lrg1, Vegf-a, and IL-10 as histone H3K18 lactylation target genes. The increased modification and expression levels of these target genes post-MI were verified by chromatin immunoprecipitation-qPCR and reverse transcription-qPCR. RESULTS: We demonstrated that histone lactylation regulates the anti-inflammatory and pro-angiogenic dual activities of monocyte-macrophages by facilitating reparative gene transcription and confirmed that histone lactylation favors a reparative environment and improves cardiac function post-MI. Furthermore, we explored the potential positive role of monocyte histone lactylation in reperfused MI. Mechanistically, we provided new evidence that monocytes undergo metabolic reprogramming in the early stage of MI and demonstrated that dysregulated glycolysis and MCT1 (monocarboxylate transporter 1)-mediated lactate transport promote histone lactylation. Finally, we revealed the catalytic effect of IL (interleukin)-1ß-dependent GCN5 (general control non-depressible 5) recruitment on histone H3K18 lactylation and elucidated its potential role as an upstream regulatory element in the regulation of monocyte histone lactylation and downstream reparative gene expression post-MI. CONCLUSIONS: Histone lactylation promotes early remote activation of the reparative transcriptional response in monocytes, which is essential for the establishment of immune homeostasis and timely activation of the cardiac repair process post-MI.

Long Noncoding RNA Gpr137b-ps Promotes Advanced Atherosclerosis via the Regulation of Autophagy in Macrophages.

BACKGROUND: Current therapies cannot completely reverse advanced atherosclerosis. High levels of amino acids, induced by Western diet, stimulate mTORC1 (mammalian target of rapamycin complex 1)-autophagy defects in macrophages, accelerating atherosclerotic plaque progression. In addition, autophagy-lysosomal dysfunction contributes to plaque necrotic core enlargement and lipid accumulation. Therefore, it is essential to investigate the novel mechanism and molecules to reverse amino acid-mTORC1-autophagy signaling dysfunction in macrophages of patients with advanced atherosclerosis. METHODS: We observed that Gpr137b-ps (G-protein-coupled receptor 137B, pseudogene) was upregulated in advanced atherosclerotic plaques. The effect of Gpr137b-ps on the progression of atherosclerosis was studied by generating advanced plaques in ApoE-/- mice with cardiac-specific knockout of Gpr137b-ps. Bone marrow-derived macrophages and mouse mononuclear macrophage cell line RAW264.7 cells were subjected to starvation or amino acid stimulation to study amino acid-mTORC1-autophagy signaling. Using both gain- and loss-of-function approaches, we explored the mechanism of Gpr137b-ps-regulated autophagy. RESULTS: Our results demonstrated that Gpr137b-ps deficiency led to enhanced autophagy in macrophages and reduced atherosclerotic lesions, characterized by fewer necrotic cores and less lipid accumulation. Knockdown of Gpr137b-ps increased autophagy and prevented amino acid-induced mTORC1 signaling activation. As the downstream binding protein of Gpr137b-ps, HSC70 (heat shock cognate 70) rescued the impaired autophagy induced by Gpr137b-ps. Furthermore, Gpr137b-ps interfered with the HSC70 binding to G3BP (Ras GTPase-activating protein-binding protein), which tethers the TSC (tuberous sclerosis complex) complex to lysosomes and suppresses mTORC1 signaling. In addition to verifying that the NTF2 (nuclear transport factor 2) domain of G3BP binds to HSC70 by in vitro protein synthesis, we further demonstrated that HSC70 binds to the NTF2 domain of G3BP through its W90-F92 motif by using computational modeling. CONCLUSIONS: These findings reveal that Gpr137b-ps plays an essential role in the regulation of macrophage autophagy, which is crucial for the progression of advanced atherosclerosis. Gpr137b-ps impairs the interaction of HSC70 with G3BP to regulate amino acid-mTORC1-autophagy signaling, and these results provide a new potential therapeutic direction for the treatment of advanced atherosclerosis.

Transient simulation of the electrical hysteresis in a metal/polymer/metal nanostructure.

The time-dependent quantum transportation through a metal/polymer/metal system is theoretically investigated on the basis of a Su-Schrieffer-Heeger model combined with the hierarchical equations of motion formalism. Using a non-adiabatic dynamical method, the evolution of the electron subspace and lattice atoms with time can be obtained. It is found that the calculated transient currents vary with time and reach stable values after a response time under the bias voltages. However, the stable current as the system reaches its dynamical steady state exhibits a discrepancy between two sweep directions of the bias voltage, which results in pronounced electrical hysteresis loops in the current-voltage curve. By analyzing the evolution of instantaneous energy eigenstates, the occupation number of the instantaneous eigenstates, and the lattice of the polymer, we show that the formation of excitons and the delay of their annihilation are responsible for the hysteretic current-voltage characteristics, where electron-phonon interactions play the key factor. Furthermore, the hysteresis width and amplitude can also be modulated by the strength of the electron-phonon coupling, level-width broadening function, and temperature. We hope these results about past condition-dependent switching performance at a sweep voltage can provide further insight into some of the basic issues of interest in hysteresis processes in conducting polymers.

Predicting the impacts of urban development on urban thermal environment using machine learning algorithms in Nanjing, China.

The urban thermal environment undergoes significant influences from changes in land use/land cover (LULC). This article uses CA-ANN and ANN algorithms to forecast LULC and changes in the urban thermal environment in Nanjing for the years 2030 and 2040. It investigates the interplay between LULC changes, land surface temperature (LST), and the urban thermal field variance index (UTFVI). The findings reveal that urban land exhibited a significant expansion trend from 2000 to 2019, reaching 1083.43 km2 in 2019. The forecast indicates that urban land may increase by 8.79% and 10.92% by 2030 and 2040, respectively. Conversely, vegetation and bare land may decrease. The LST is likely to continue to rise, accompanied by a significant expansion of the high temperature range and a contraction of the low temperature range. By 2030 and 2040, the area with LST<20 °C is likely to decrease by 2.17% and 3.19%, while the area with LST>30 °C is likely to expand by 5.68% and 8.08%, respectively. The UTFVI area of urban land may decrease at none and middle levels but may notably expand at stronger and strongest levels. The areas with UTFVI at none, weak, and middle levels show a declining trend, while the increase in UTFVI at the strong level may exceed 46.29% and the strongest level of UTFVI may continue to expand. This study offers new insights into urban sustainable development and thermal environment governance.

Development of unigene-derived SSR markers from RNA-seq data of Uraria lagopodioides (Fabaceae) and their application in the genus Uraria Desv. (Fabaceae).

BACKGROUND: Uraria Desv. belongs to the tribe Desmodieae (Fabaceae), a group of legume plants, some of which have medicinal properties. However, due to a lack of genomic information, the interspecific relationships, genetic diversity, population genetics, and identification of functional genes within Uraria species are still unclear. RESULTS: Using RNA-Seq, a total of 66,026 Uraria lagopodioides unigenes with a total sequence content of 52,171,904 bp were obtained via de novo assembly and annotated using GO, KEGG, and KOG databases. 17,740 SSRs were identified from a set of 66,026 unigenes. Cross-species amplification showed that 54 out of 150 potential unigene-derived SSRs were transferable in Uraria, of which 19 polymorphic SSRs were developed. Cluster analysis based on polymorphisms successfully distinguished seven Uraria species and revealed their interspecific relationships. Seventeen samples of seven Uraria species were clustered into two monophyletic clades, and phylogenetic relationships of Uraria species based on unigene-derived SSRs were consistent with classifications based on morphological characteristics. CONCLUSIONS: Unigenes annotated in the present study will provide new insights into the functional genomics of Uraria species. Meanwhile, the unigene-derived SSR markers developed here will be invaluable for assessing the genetic diversity and evolutionary history of Uraria and relatives.

The effect of the intramolecular disorder on hot exciton dynamics in polymer solar cells.

In polymer solar cells (PSCs), the contribution of hot excitons to charge generation is strongly limited by their relatively low yield and ultrafast internal conversion (IC) process. In recent years, different strategies have been proposed to modulate the hot exciton dynamics, but a direct correlation between the microscopic properties of the polymer and hot exciton dynamics is still not completely clear. Here, we theoretically investigate the effect of intramolecular disorder, including the diagonal disorder (DD) and off-diagonal disorder (ODD), on the hot exciton dynamics based on the tight-binding model calculations. We find that the effect of ODD on the hot exciton yield is more significant than that of DD. In addition, we find that the IC relaxation time of hot excitons depends nonmonotonically on the intensity of DD and ODD, indicating that the intramolecular disorder can modulate the competitive relationship between the spontaneous dissociation of hot excitons and the IC process. This work provides a guide for promoting charge generation in PSCs dominated by hot exciton dissociation.

Mettl14 mediates the inflammatory response of macrophages in atherosclerosis through the NF-κB/IL-6 signaling pathway.

The inflammatory response of macrophages has been reported to play a critical role in atherosclerosis. The inflammatory state of macrophages is modified by epigenetic reprogramming. m6A RNA methylation is an epigenetic modification of RNAs. However, little is known about the potential roles and underlying mechanisms of m6A modification in macrophage inflammation. Herein, we showed that the expression of the m6A modification "writer" Mettl14 was increased in coronary heart disease and LPS-stimulated THP-1 cells. Knockdown of Mettl14 promoted M2 polarization of macrophages, inhibited foam cell formation and decreased migration. Mechanistically, the expression of Myd88 and IL-6 was decreased in Mettl14 knockdown cells. Through m6A modification, Mettl14 regulated the stability of Myd88 mRNA. Furthermore, Myd88 affected the transcription of IL-6 via the distribution of p65 in nuclei rather than directly regulating the expression of IL-6 through m6A modification. In vivo, Mettl14 gene knockout significantly reduced the inflammatory response of macrophages and the development of atherosclerotic plaques. Taken together, our data demonstrate that Mettl14 plays a vital role in macrophage inflammation in atherosclerosis via the NF-κB/IL-6 signaling pathway, suggesting that Mettl14 may be a promising therapeutic target for the clinical treatment of atherosclerosis.

High-order dipolar annulations with metal-containing reactive dipoles.

Medium-sized heterocycles are widespread among a spectrum of structurally intriguing and biologically significant natural products and synthetic pharmaceuticals. Metal-catalyzed high-order dipolar annulations resembling reactions of metal-containing reactive dipoles with dipolarophiles constitute a highly efficient and flexible strategy for constructing medium-sized heterocycles. Mechanistically, these annulation reactions usually proceeding through stepwise pathways are different from the classic high-order pericyclic reactions that follow the Woodward-Hoffman rules. More significantly, asymmetric high-order dipolar annulations using chiral organometallic catalysts have been proven successful for constructing chiral medium-sized heterocycles with high enantio- and diastereoselectivity. This review highlights the impressive advances in this area and is focused on the reactivity, scope, mechanisms and applications of high-order dipolar annulation reactions.

Fluorophore-conjugated 4-1BB antibody enables early detection of T-cell responses in inflammatory arthritis via NIRF imaging.

PURPOSE: We first developed a 4-1BB-targeted optical probe, named IRDye-680RD-4-1BB mAb (monoclonal antibody), and evaluated its value for the detection of 4-1BB+ activated T cells in vivo as well as the diagnosis of rheumatoid arthritis (RA) in an adjuvant-induced arthritis (AIA) mouse model. METHODS: The 4-1BB expression pattern was analysed by flow cytometry and immunofluorescence (IF) staining. The 4-1BB mAb was conjugated with IRDye-680RD NHS ester, and characterized via fluorescence spectrum. A cell-binding assay was also performed to assess the interaction of this probe with activated and naïve murine T cells. Longitudinal near-infrared fluorescence (NIRF) imaging of the probe was performed at 6, 24, 48, 72, and 96 h after probe administration. RESULTS: 4-1BB expression was highly upregulated during the pathogenesis of RA. Good colocalization was also observed between CD3 and 4-1BB by IF staining and t-SNE (T-distributed stochastic neighbour embedding) analysis, which indicates that 4-1BB was mainly expressed on T cells. Compared to the control group, a significantly higher signal was observed in the right hind paw (RP) of mice with AIA at all time points. The ex vivo biodistribution study results were consistent with the in vivo NIRF imaging results, which validated the accuracy of the region of interest (ROI) measurements. The sensitivity against 100% specificity observed in the receiver operator characteristic (ROC) curve analysis could distinguish the AIA group from the control group at all time points, indicating the value of IRDye-680RD-4-1BB mAb for RA diagnosis. CONCLUSION: We successfully developed a novel optical imaging probe, named IRDye-680RD-4-1BB mAb, for tracking 4-1BB+ activated T cells in vivo, and 4-1BB NIRF imaging is a promising strategy for noninvasively detecting the pathogenesis of RA.

The spatial spillover effect and nonlinear relationship analysis between land resource misallocation and environmental pollution: Evidence from China.

Compared with other countries, China's local governments often adopt the land supply strategy of "low price and sufficient supply" for industrial land and "high price and limited supply" for commercial land in the allocation of land resources. The allocation of land resources is an important means to promote the rapid development of China's economy, and the impacts of land resource misallocation (LRM) on environmental pollution are increasingly apparent. This paper uses panel data from 30 provinces in China from 2009 to 2018 to discuss the relationship between LRM and environmental pollution. The ratio of the average price of commercial land to the average price of industrial land is used to measure the degree of LRM. The Ordinary Least Squares (OLS), spatial Durbin model (SDM), threshold model, and mediation effect model are used to study the direct effect, spatial spillover effect, nonlinear relationship, and conduction mechanism of LRM on environmental pollution. The results show that LRM significantly aggravated environmental pollution. This conclusion still holds after robustness tests including the substitution of dependent variables and IV estimates. The LRM aggravates environmental pollution through industrial structure and technological progress. Interestingly, the impact of LRM on environmental pollution also has a significant positive spatial spillover effect in adjacent regions. In addition, there is also evidence that the adverse effect of LRM on environmental pollution is nonlinear at different levels of industrial structure and technological progress. The threshold model shows that with the optimization of the industrial structure, the impact of LRM on environmental pollution shows a weakening trend of "inverted V-shaped", and with the advancement of technology, the impact of LRM on environmental pollution presents an "S-shaped" changing trend of "strong-weak-strong".

Macrophage-Enriched lncRNA RAPIA: A Novel Therapeutic Target for Atherosclerosis.

OBJECTIVE: Despite the current antiatherosclerotic and antithrombotic therapies, the incidence of advanced atherosclerosis-associated clinical events remains high. Whether long noncoding RNAs (lncRNAs) affect the progression of atherosclerosis and whether they are potential targets for the treatment of advanced atherosclerosis are poorly understood. Approach and Results: The progression of atherosclerotic lesions was accompanied by dynamic alterations in lncRNA expression, as revealed by RNA sequencing and quantitative polymerase chain reaction. Among the dynamically changing lncRNAs, we identified a novel lncRNA, lncRNA Associated with the Progression and Intervention of Atherosclerosis (RAPIA), that was highly expressed in advanced atherosclerotic lesions and in macrophages. Inhibition of RAPIA in vivo not only repressed the progression of atherosclerosis but also exerted atheroprotective effects similar to those of atorvastatin on advanced atherosclerotic plaques that had already formed. In vitro assays demonstrated that RAPIA promoted proliferation and reduced apoptosis of macrophages. A molecular sponge interaction between RAPIA and microRNA-183-5p was demonstrated by dual-luciferase reporter and RNA immunoprecipitation assays. Rescue assays indicated that RAPIA functioned at least in part by targeting the microRNA-183-5p/ITGB1 (integrin ß1) pathway in macrophages. In addition, the transcription factor FoxO1 (forkhead box O1) could bind to the RAPIA promoter region and facilitate the expression of RAPIA. CONCLUSIONS: The progression of atherosclerotic lesions was accompanied by dynamic changes in the expression of lncRNAs. Inhibition of the pivotal lncRNA RAPIA may be a novel preventive and therapeutic strategy for advanced atherosclerosis, especially in patients resistant or intolerant to statins.

Methotrexate Therapy Promotes Cell Coverage and Stability in in-Stent Neointima.

PURPOSE: Anti-proliferative drugs released from drug-eluting stents delay cell coverage and vascular healing, which increases the risk of late stent thrombosis. We assessed the potential effects of systemic methotrexate (MTX) on cell coverage, vascular healing and inflammation activation in vivo and in vitro. METHODS: We applied MTX in the right common carotid artery in a rabbit stenting model to determine the impact on cell coverage and inflammation activation using a serial optical coherence tomography (OCT) analysis and elucidated the molecular mechanism of MTX in human umbilical vein endothelial cells (HUVECs). RESULTS: Low-dose MTX promoted the development of cell coverage and vascular healing, which was associated with fewer uncovered struts (%) and cross-sections with any uncovered struts (%) at 4 weeks of stenting. The MTX group also exhibited lower rates of heterogeneity, microvessels and per-strut low-signal-intensity layers, indicating neointimal instability at 12 weeks of stenting. In vitro, low-dose MTX strongly inhibited HUVEC apoptosis, promoted proliferation and inhibited inflammatory activation by targeting the phosphoinositide 3-kinase (PI3K)/AKT signalling pathway. CONCLUSION: Low-dose MTX may be a key means of promoting early cell coverage via the inhibition of the inflammatory response and stability of neointima by targeting inflammatory pathways after stent implantation.

Circulating Exosomes Control CD4+ T Cell Immunometabolic Functions via the Transfer of miR-142 as a Novel Mediator in Myocarditis.

CD4+ T cells undergo immunometabolic activation to mount an immunogenic response during experimental autoimmune myocarditis (EAM). Exosomes are considered key messengers mediating multiple T cell functions in autoimmune responses. However, the role of circulating exosomes in EAM immunopathogenesis and CD4+ T cell dysfunction remains elusive. Our objective was to elucidate the mechanism of action for circulating exosomes in EAM pathogenesis. We found that serum exosomes harvested from EAM mice induced CD4+ T cell immunometabolic dysfunction. Treatment with the exosome inhibitor GW4869 protected mice from developing EAM, underlying that exosomes are indispensable for the pathogenesis of EAM. Furthermore, by transfer of EAM exosomes, we confirmed that circulating exosomes initiate the T cell pathological immune response, driving the EAM pathological process. Mechanistically, EAM-circulating exosomes selectively loaded abundant microRNA (miR)-142. We confirmed methyl-CpG binding domain protein 2 (MBD2) and suppressor of cytokine signaling 1 (SOCS1) as functional target genes of miR-142. The miR-142/MBD2/MYC and miR-142/SOCS1 communication axes are critical to exosome-mediated immunometabolic turbulence. Moreover, the in vivo injection of the miR-142 inhibitor alleviated cardiac injury in EAM mice. This effect was abrogated by pretreatment with EAM exosomes. Collectively, our results indicate a newly endogenous mechanism whereby circulating exosomes regulate CD4+ T cell immunometabolic dysfunction and EAM pathogenesis via cargo miR-142.

Circular RNA circSnx5 Controls Immunogenicity of Dendritic Cells through the miR-544/SOCS1 Axis and PU.1 Activity Regulation.

Dendritic cells (DCs) can orchestrate either immunogenic or tolerogenic responses to relay information on the functional state. Emerging studies indicate that circular RNAs (circRNAs) are involved in immunity; however, it remains unclear whether they govern DC development and function at the transcriptional level. In this study, we identified a central role for a novel circRNA, circSnx5, in modulating DC-driven immunity and tolerance. Ectopic circSnx5 suppresses DC activation and promotes the development of tolerogenic functions of DCs, while circSnx5 knockdown promotes their activation and inflammatory phenotype. Mechanistically, circSnx5 can act as a miR-544 sponge to attenuate miRNA-mediated target depression on suppressor of cytokine signaling 1 (SOCS1) and inhibit nuclear translocation of PU.1, regulating DC activation and function. Furthermore, the main splicing factors (SFs) were identified in DCs, of which heterogeneous nuclear ribonucleoprotein (hnRNP) C was essential for circSnx5 generation. Moreover, our data demonstrated that vaccination with circSnx5-conditioned DCs prolonged cardiac allograft survival in mice and alleviated experimental autoimmune myocarditis. Taken together, our results revealed circSnx5 as a key modulator to fine-tune DC function, suggesting that circSnx5 may serve as a potential therapeutic avenue for immune-related diseases.

Nurses' psychological changes and coping strategies during home isolation for the 2019 novel coronavirus in China: A qualitative study.

AIMS: To explore the psychological changes of nurses during home isolation, the factors that related with these changes, and coping strategies in home isolation during the epidemic of COVID-19 in China. DESIGN: A qualitative study based on grounded theory. METHODS: Individual semi-structured telephone interviews were conducted from January 2020-February 2020 with 10 nurses who were isolated at home sharing the experiences of the epidemic of COVID-19. All interviews were audio recorded, transcribed, and analysed using constant comparative data analysis. RESULTS: Analyses of the collected data reveal that the psychological changes of nurses during home isolation reflect a complex, dynamic, and gradually adaptive process that was affected by many factors. Nurses had many negative emotional reactions in the early stages of isolation and positive emotions gradually increased during home isolation. After release from home isolation, they become more confident and calm after. Six categories of coping strategies were identified, including reasoned cognition; autosuggestion; develop healthy protective behaviours; shifting attention; social support; and the power of a role model. CONCLUSIONS: The study provides a better understanding of the psychological changes and the coping strategies used among nurses isolated at home. It is necessary to pay more attention to negative emotions in the early stages of home isolation to help nurses adjust quickly. The coping strategies used by nurses are likely to help those in home isolation reduce negative psychological changes and experience more optimal self-adjustment. IMPACT: This study explored the psychological changes and coping strategies of home isolation among nurses, providing useful advice for psychologists to develop psychological crisis interventions to help individuals reduce negative psychological and have more actively coping strategies when faced sudden stressful infectious diseases.

Coarse-to-Fine Hand-Object Pose Estimation with Interaction-Aware Graph Convolutional Network.

The analysis of hand-object poses from RGB images is important for understanding and imitating human behavior and acts as a key factor in various applications. In this paper, we propose a novel coarse-to-fine two-stage framework for hand-object pose estimation, which explicitly models hand-object relations in 3D pose refinement rather than in the process of converting 2D poses to 3D poses. Specifically, in the coarse stage, 2D heatmaps of hand and object keypoints are obtained from RGB image and subsequently fed into pose regressor to derive coarse 3D poses. As for the fine stage, an interaction-aware graph convolutional network called InterGCN is introduced to perform pose refinement by fully leveraging the hand-object relations in 3D context. One major challenge in 3D pose refinement lies in the fact that relations between hand and object change dynamically according to different HOI scenarios. In response to this issue, we leverage both general and interaction-specific relation graphs to significantly enhance the capacity of the network to cover variations of HOI scenarios for successful 3D pose refinement. Extensive experiments demonstrate state-of-the-art performance of our approach on benchmark hand-object datasets.

CNN-Based Volume Flow Rate Prediction of Oil-Gas-Water Three-Phase Intermittent Flow from Multiple Sensors.

In this paper, we propose a deep-learning-based method using a convolutional neural network (CNN) to predict the volume flow rates of individual phases in the oil-gas-water three-phase intermittent flow simultaneously by analyzing the measurement data from multiple sensors, including a temperature sensor, a pressure sensor, a Venturi tube and a microwave sensor. To build datasets, a series of experiments for the oil-gas-water three-phase intermittent flow in a horizontal pipe, in which gas volume fraction and water-in-liquid ratio ranges are 23.77-94.45% and 14.95-86.97%, respectively, and gas flow superficial velocity and liquid flow superficial velocity ranges are 0.66-5.23 and 0.27-2.14 m/s, respectively, have been carried out on a test loop pipeline. The preliminary results indicate that the model can provide relative prediction errors on the testing-1 dataset for the volume flow rates of oil-phase, gas-phase and water-phase within ±10% with 94.49%, 92.56% and 95.71% confidence levels, respectively. Additionally, the prediction results on the testing-2 dataset also demonstrate the generalization ability of the model. The consuming time of a prediction with one sample is 0.43 s on an Intel Xeon CPU E5-2678 v3, and 0.01 s on an NVIDIA GeForce GTX 1080 Ti GPU. Hence, the proposed CNN-based prediction model, which can fulfill the real-time application requirements in the petroleum industry, reveals the potential of using deep learning to obtain accurate results in the multiphase flow measurement field.

A Wet Gas Metering System Based on the Extended-Throat Venturi Tube.

Although the use of a classical Venturi tube for wet gas metering has been extensively studied in the literature, the use of an extended-throat Venturi (ETV) tube has rarely been reported since its first proposal by J. R. Fincke in 1999. The structure of an ETV is very simple, but due to the complexity of multiphase flow, its theoretical model has not been fully established yet. Therefore, in this paper theoretical models have been developed for the convergent and throat sections of an ETV, and the gradients of front and rear differential pressures are derived analytically. Several flowrate algorithms have been proposed and compared with the existing ones. Among them, the iteration algorithm is found to be the best. A reasonable explanation is provided for its performance. The relationship between the differential pressure gradient and the flowrate relative error is also studied, such that the relative error distributions varying with ETV measured flowrates can be derived. The gas flowrate error of ETV increases with the liquid content whilst the liquid flowrate error of ETV decreases with the liquid content, and the relative errors of liquid flowrate are generally 2 to 3 times larger than that of the gas flowrate. Finally, the ETV tends to be more accurate than the classical Venturi tube. The ETV can be designed more compact under the same signal intensity due to its significantly higher velocity in the throat section.

A Novel Multi-Sensor Fusion Algorithm Based on Uncertainty Analysis.

During the research and development of multiphase flowmeters, errors are often used to evaluate the advantages and disadvantages of different devices and algorithms, whilst an in-depth uncertainty analysis is seldom carried out. However, limited information is sometimes revealed from the errors, especially when the test data are scant, and this makes an in-depth comparison of different algorithms impossible. In response to this problem, three combinations of sensing methods are implemented, which are the "capacitance and cross-correlation", the "cross-correlation and differential pressure" and the "differential pressure and capacitance" respectively. The analytical expressions of the gas/liquid flowrate and the associated standard uncertainty have been derived, and Monte Carlo simulations are carried out to determine the desired probability density function. The results obtained through these two approaches are basically the same. Thereafter, the sources of uncertainty for each combination are traced and their respective variations with flowrates are analyzed. Further, the relationship between errors and uncertainty is studied, which demonstrates that the two uncertainty analysis approaches can be a powerful tool for error prediction. Finally, a novel multi-sensor fusion algorithm based on the uncertainty analysis is proposed. This algorithm can minimize the standard uncertainty over the whole flowrate range and thus reduces the measurement error.

Evaluation of the Deterioration State of Archaeological Wooden Artifacts: A Nondestructive Protocol based on Direct Analysis in Real Time - Mass Spectrometry (DART-MS) Coupled to Chemometrics.

Evaluating the deterioration state of archeological wood is obligatory before the preservation of archeological wooden artifacts. Herein, a nondestructive, accurate, and rapid methodology is first developed via direct analysis in real time-mass spectrometry (DART-MS) with chemometrics to classify archeological wood and recent wood into 3 groups according to their deterioration states. As water in wooden artifacts probably affected the ion fragmentation process during DART-MS, ions responsible for evaluating the deterioration state were separately screened toward waterlogged archeological wood and dried archeological wood by partial least-squares discriminant analysis (PLS-DA). The well-defined separation of severely decayed archeological wood, moderately decayed archeological wood and recent wood was revealed in PLS-DA models. Twenty and 27 wood fragment ions were further screened as key variables to evaluate the deterioration state of waterlogged archeological wood and dried archeological wood, respectively. They were tentatively identified as ions of lignin monomeric compositions, lignin dimers, lignin trimers, and oligosaccharides. Results strongly suggested that differences in the structure and relative abundances of wood cell wall components accounts for the evaluation of deterioration state by DART-MS coupled to chemometrics. PLS-DA models provided R2Y = 0.836, Q2 = 0.817, and R2Y = 0.754, Q2 = 0.682 were then established separately using mass spectral fingerprints of respective potential predictive wood fragment ions. Furthermore, archeological woods, consisting of Castanopsis, Quercus, Idesia, Populus, and Cunninghamia species and with an average MWC range of 103-465%, were used as an external validation set and evaluated with the methodology developed herein and the MWC criteria. Results showed that DART-MS coupled to chemometrics could accurately predict the inhomogeneous deterioration states of archeological wooden artifacts and avoid the interference of inorganic deposits, in comparison with the MWC criteria.