Pilot-scale testing on catalytic hydrolysis of carbonyl sulfur combined with absorption-oxidation of H2S for blast furnace gas purification.

About 70% of the flue gas in the iron-steel industry has achieved multi-pollutant ultra-low emissions in China until 2023, and then the blast furnace gas purification has become the control step and bottleneck. Our research group has designed and constructed the world's first blast furnace gas desulfurization pilot plant with the scale of 2000 Nm3/h in October 2021. The pilot plant is a two-step combined desulfurization device including catalytic hydrolysis of carbonyl sulfur (COS) and absorption-oxidation of H2S, continuously running for 120 days. In the hydrolysis system, one reason for catalyst deactivation has been verified from the sulfur deposition. HCN in blast furnace gas can be hydrolyzed on the hydrolysis catalyst to produce the nitrogen deposition, which is one of the reasons for catalyst deactivation and has never been found in previous studies. The deposition forms of S and N elements are determined, S element forms elemental sulfur and sulfate, while N element forms -NH2 and NH4+. In the absorption-oxidation system, the O2 loading and the residence time have been optimized to control the oxidation of HS- to produce elemental sulfur instead of by-product S2O32-. The balance and distribution of S and N elements have been calculated for the whole multi-phase system, approximately 84.4% of the sulfur is converted to solid sulfur product, about 1.3% of the sulfur and 19.2% of N element are deposited on the hydrolysis catalyst. The pilot plant provides technical support for multi-pollutant control of blast furnace.

Strong, Spontaneous, and Self-Healing Poly(Ionic Liquid) Elastomer Underwater Adhesive with Borate Ester Dynamic Crosslinking.

Adhesion in aqueous environments is often hindered by the water layer on the surface of the substrate due to the water sensitivity of the adhesive, greatly limiting the application environment. Here, a borate ester dynamically crosslinked poly(ionic liquid) elastomer adhesive (PIEA) with high strength, toughness, self-healing abilities, and ionic conductivity is synthesized by copolymerizing hydrophobic ionic liquid monomer ([HPVIm][TFSI]) and 2-methoxyethyl acrylate (MEA). The adhesion strength of PIEA can increase spontaneously from almost no adhesion to 314 kPa after 12 h without any external preloading due to the dissociation of the borate ester in water, leading to noncovalent interactions between the hydroxyl groups of PIEA and the substrate. Additionally, PIEA can be developed for soft sensors or ion electrodes to enable underwater detection and communication. This strategy offers broad application potential for the development of novel underwater smart adhesives.

Orthogonality of polarization superposition based on polarization holography.

We propose a polarization superposition orthogonal theory based on tensor polarization holography. Based on this theory, the holographic multiplexing capability can be improved measurably. The orthogonality of polarization waves is characterized by the null reconstruction in polarization holography, achieved through the superposition of multiple basic polarization reference waves. This paper analyzes the orthogonality of linear polarization wave superposition and circular polarization wave superposition using the tensor polarization holography theory. Using the polarized holography multiplexing technique, we experimentally verify the orthogonality of polarization wave superposition. Our experimental results align with the theoretical analysis, indicating potential applications in polarization encoding and decoding by this theory, thereby diversifying optical encryption technology Additionally, we demonstrate that polarization superposition orthogonality holds significant promise for optical control technology.

A machine learning algorithm to explore the drivers of carbon emissions in Chinese cities.

As the world's largest energy consumer and carbon emitter, the task of carbon emission reduction is imminent. In order to realize the dual-carbon goal at an early date, it is necessary to study the key factors affecting China's carbon emissions and their non-linear relationships. This paper compares the performance of six machine learning algorithms to that of traditional econometric models in predicting carbon emissions in China from 2011 to 2020 using panel data from 254 cities in China. Specifically, it analyzes the comparative importance of domestic economic, external economic, and policy uncertainty factors as well as the nonparametric relationship between these factors and carbon emissions based on the Extra-trees model. Results show that energy consumption (ENC) remains the root cause of increased carbon emissions among domestic economic factors, although government intervention (GOV) and digital finance (DIG) can significantly reduce it. Next, among the external economic and policy uncertainty factors, foreign direct investment (FDI) and economic policy uncertainty (EPU) are important factors influencing carbon emissions, and the partial dependence plots (PDPs) confirm the pollution haven hypothesis and also reveal the role of EPU in reducing carbon emissions. The heterogeneity of factors affecting carbon emissions is also analyzed under different city sizes, and it is found that ENC is a common driving factor in cities of different sizes, but there are some differences. Finally, appropriate policy recommendations are proposed by us to help China move rapidly towards a green and sustainable development path.

Exploration of physical activity, sedentary behavior and insulin level among short sleepers.

Background: Sufficient physical activity and sleep duration are essential for overall health. While one-third of the US population reports short sleep (<7 h), which is proven to link with negative health status. Current evidence on the relationship between physical activity, sedentary behavior, and serum insulin level in short sleep groups is limited. Methods: The National Health and Nutrition Examination Survey (NHANES) was used to conduct this cross-sectional study of 8,494 adults (NHANES) 2007-2018. Serum insulin was quantitatively tested by human insulin immunoassay. Short sleep conditions were defined as ≤7 h per night. Physical activity conditions, including work activity, recreational activity, and sedentary behavior, were self-reported in NHANES by the Physical Activity Questionnaire using a 7-day recall method. The main analyses utilized weighted linear regression models due to the complex multistage sampling design of NHANES. Subgroup analysis and the influence of different lipid indices were explored in this study. In addition, a sensitivity analysis of participants without diabetes was conducted. Results: In fully adjusted models, increased levels of work and recreational activity significantly reduced insulin levels, with ß values 95% CI = -0.002 (-0.003, 0.001) and ß values 95% CI = -0.008 (-0.012, -0.003), respectively. However, sedentary behavior was positively associated with insulin levels, with a ß value 95% CI =0.022 (0.009, 0.034). The sensitivity analysis further confirmed the benefits of recreational activity in controlling insulin levels. Through sex stratification analysis, it seemed that physical activity was more obviously impacted in the male than female groups. Conclusions: Overall, our analysis demonstrates that in short sleepers, an increased level of work and recreational activity is beneficial to control the insulin level, and more sedentary time is harmful. However, this association might be discrepant in different sexes and different levels of lipid indices.

Pyramid-YOLOv8: a detection algorithm for precise detection of rice leaf blast.

Rice blast is the primary disease affecting rice yield and quality, and its effective detection is essential to ensure rice yield and promote sustainable agricultural production. To address traditional disease detection methods' time-consuming and inefficient nature, we proposed a method called Pyramid-YOLOv8 for rapid and accurate rice leaf blast disease detection in this study. The algorithm is built on the YOLOv8x network framework and features a multi-attention feature fusion network structure. This structure enhances the original feature pyramid structure and works with an additional detection head for improved performance. Additionally, this study designs a lightweight C2F-Pyramid module to enhance the model's computational efficiency. In the comparison experiments, Pyramid-YOLOv8 shows excellent performance with a mean Average Precision (mAP) of 84.3%, which is an improvement of 9.9%, 4.3%, 7.4%, 6.1%, 1.5%, 3.7%, and 8.2% compared to the models Faster-RCNN, RT-DETR, YOLOv3-SPP, YOLOv5x, YOLOv9e, and YOLOv10x, respectively. Additionally, it reaches a detection speed of 62.5 FPS; the model comprises only 42.0 M parameters. Meanwhile, the model size and Floating Point Operations (FLOPs) are reduced by 41.7% and 23.8%, respectively. These results demonstrate the high efficiency of Pyramid-YOLOv8 in detecting rice leaf blast. In summary, the Pyramid-YOLOv8 algorithm developed in this study offers a robust theoretical foundation for rice disease detection and introduces a new perspective on disease management and prevention strategies in agricultural production.

SOX2 interacts with hnRNPK to modulate alternative splicing in mouse embryonic stem cells.

BACKGROUND: SOX2 is a determinant transcription factor that governs the balance between stemness and differentiation by influencing transcription and splicing programs. The role of SOX2 is intricately shaped by its interactions with specific partners. In the interactome of SOX2 in mouse embryonic stem cells (mESCs), there is a cohort of heterogeneous nuclear ribonucleoproteins (hnRNPs) that contributes to multiple facets of gene expression regulation. However, the cross-talk between hnRNPs and SOX2 in gene expression regulation remains unclear. RESULTS: Here we demonstrate the indispensable role of the co-existence of SOX2 and heterogeneous nuclear ribonucleoprotein K (hnRNPK) in the maintenance of pluripotency in mESCs. While hnRNPK directly interacts with the SOX2-HMG DNA-binding domain and induces the collapse of the transcriptional repressor 7SK small nuclear ribonucleoprotein (7SK snRNP), hnRNPK does not influence SOX2-mediated transcription, either by modulating the interaction between SOX2 and its target cis-regulatory elements or by facilitating transcription elongation as indicated by the RNA-seq analysis. Notably, hnRNPK enhances the interaction of SOX2 with target pre-mRNAs and collaborates with SOX2 in regulating the alternative splicing of a subset of pluripotency genes. CONCLUSIONS: These data reveal that SOX2 and hnRNPK have a direct protein-protein interaction, and shed light on the molecular mechanisms by which hnRNPK collaborates with SOX2 in alternative splicing in mESCs.

Transcriptomic and Physiological Analyses for the Role of Hormones and Sugar in Axillary Bud Development of Wild Strawberry Stolon.

Strawberries are mainly propagated by stolons, which can be divided into monopodial and sympodial types. Monopodial stolons consistently produce ramets at each node following the initial single dormant bud, whereas sympodial stolons develop a dormant bud before each ramet. Sympodial stolon encompasses both dormant buds and ramet buds, making it suitable for studying the formation mechanism of different stolon types. In this study, we utilized sympodial stolons from Fragaria nilgerrensis as materials and explored the mechanisms underlying sympodial stolon development through transcriptomic and phytohormonal analyses. The transcriptome results unveiled that auxin, cytokinin, and sugars likely act as main regulators. Endogenous hormone analysis revealed that the inactivation of auxin could influence bud dormancy. Exogenous cytokinin application primarily induced dormant buds to develop into secondary stolons, with the proportion of ramet formation being very low, less than 10%. Furthermore, weighted gene co-expression network analysis identified key genes involved in ramet formation, including auxin transport and response genes, the cytokinin activation gene LOG1, and glucose transport genes SWEET1 and SFP2. Consistently, in vitro cultivation experiments confirmed that glucose enhances the transition of dormant buds into ramets within two days. Collectively, cytokinin and glucose act as dormant breakers, with cytokinin mainly driving secondary stolon formation and glucose promoting ramet generation. This study improved our understanding of stolon patterning and bud development in the sympodial stolon of strawberries.

Molecular characterization of QTL for grain zinc and iron concentrations in wheat landrace Chinese Spring.

KEY MESSAGE: Three stable QTL for grain zinc concentration were identified in wheat landrace Chinese Spring. Favorable alleles were more frequent in landraces than in modern wheat cultivars. Wheat is a major source of dietary energy for the growing world population. Developing cultivars with enriched zinc and iron can potentially alleviate human micronutrient deficiency. In this study, a recombinant inbred line (RIL) population with 245 lines derived from cross Zhou 8425B/Chinese Spring was used to detect quantitative trait loci (QTL) for grain zinc concentration (GZnC) and grain iron concentration (GFeC) across four environments. Three stable QTL for GZnC with all favorable alleles from Chinese Spring were identified on chromosomes 3BL, 5AL, and 5BL. These QTL explaining maxima of 8.7%, 5.8%, and 7.1% of phenotypic variances were validated in 125 resequenced wheat accessions encompassing both landraces and modern cultivars using six kompetitive allele specific PCR (KASP) assays. The frequencies of favorable alleles for QGZnCzc.caas-3BL, QGZnCzc.caas-5AL and QGZnCzc.caas-5BL were higher in landraces (90.4%, 68.0%, and 100.0%, respectively) compared to modern cultivars (45.9%, 35.4%, and 40.9%), suggesting they were not selected in breeding programs. Candidate gene association studies on GZnC in the cultivar panel further delimited the QTL into 8.5 Mb, 4.1 Mb, and 47.8 Mb regions containing 46, 4, and 199 candidate genes, respectively. The 5BL QTL located in a region where recombination was suppressed. Two stable and three less stable QTL for GFeC with favorable alleles also from Chinese Spring were identified on chromosomes 4BS (Rht-B1a), 4DS (Rht-D1a), 1DS, 3AS, and 6DS. This study sheds light on the genetic basis of GZnC and GFeC in Chinese Spring and provides useful molecular markers for wheat biofortification.

Incidence, mortality, and predictive factors associated with acute respiratory distress syndrome in multiple trauma patients living in high-altitude areas: a retrospective study in Shigatse.

Background: Acute respiratory distress syndrome (ARDS) is a severe complication that can lead to fatalities in multiple trauma patients. Nevertheless, the incidence rate and early prediction of ARDS among multiple trauma patients residing in high-altitude areas remain unknown. Methods: This study included a total of 168 multiple trauma patients who received treatment at Shigatse People's Hospital Intensive Care Unit (ICU) between January 1, 2019 and December 31, 2021. The clinical characteristics of the patients and the incidence rate of ARDS were assessed. Univariable and multivariable logistic regression models were employed to identify potential risk factors for ARDS, and the predictive effects of these risk factors were analyzed. Results: In the high-altitude area, the incidence of ARDS among multiple trauma patients was 37.5% (63/168), with a hospital mortality rate of 16.1% (27/168). Injury Severity Score (ISS) and thoracic injuries were identified as significant predictors for ARDS using the logistic regression model, with an area under the curve (AUC) of 0.75 and 0.75, respectively. Furthermore, a novel predictive risk score combining ISS and thoracic injuries demonstrated improved predictive ability, achieving an AUC of 0.82. Conclusions: This study presents the incidence of ARDS in multiple trauma patients residing in the Tibetan region, and identifies two critical predictive factors along with a risk score for early prediction of ARDS. These findings have the potential to enhance clinicians' ability to accurately assess the risk of ARDS and proactively prevent its onset.

Voltage Control of Multiple Electrochemical Processes during Lithium Ion Migration in NiFe2O4 Ferrite.

Li-ion-based electric field control has been attracting significant attention, since it is able to penetrate deep into materials to exhibit diverse and controllable electrochemical processes, which offer more degrees of freedom to design multifunctional devices with low power consumption. As opposed to previous studies that mainly focused on single lithiation/delithiation mechanisms, we reveal three Li-ion modulation mechanisms in the same NiFe2O4 spinel ferrite by in situ magnetometry, i.e., intercalation, conversion, and space charge, which are respectively demonstrated in high, medium, and low voltage range. During the intercalation stage, the spinel structure is preserved, and a reversible modulation of magnetization arises from the charge transfer-induced variation of Fe valence states (Fe2+/Fe3+). Conversion-driven change in magnetization is the largest up to 89 emu g-1, due to the structural and magnetic phase transitions. Although both intercalation and conversion exhibit sluggish kinetics and long response times, the space charge manifests a faster switching speed and superior durability due to its interface electrostatic effect. These results not only provide a clear and comprehensive understanding on Li-based modulation mechanisms but also facilitate multifunctional and multiscenario applications, such as multistate memory, micromagnetic actuation, artificial synapse, and energy storage.

Identification of crucial genes through WGCNA in the progression of gastric cancer.

Background: To explore the hub gene closely related to the progression of gastric cancer (GC), so as to provide a theoretical basis for revealing the therapeutic mechanism of GC. Methods: The gene expression profile and clinical data of GSE15459 in Gene Expression Omnibus (GEO) database were downloaded. The weighted gene co-expression network analysis (WGCNA) was used to screen the key modules related to GC progression. Survival analysis was used to assess the influence of hub genes on patients' outcomes. CIBERSORT analysis was used to predict the tissue infiltrating immune cells in patients. Immunohistochemical staining was conducted to further verify the expression of hub genes. Results: Through WGCNA, a total of 26 co-expression modules were constructed, in which salmon module and royalblue module had strong correlation with GC progression. The results of enrichment analysis showed that genes in the two modules were mainly involved in toll-like receptor signaling pathway, cholesterol metabolism and neuroactive ligand-receptor interaction. Six hub genes (C1QA, C1QB, C1QC, FCER1G, FPR3 and TYROBP) related to GC progression were screened. Survival analysis showed overall survival in the high expression group was significantly lower than that in the low expression group. CIBERSORT analysis revealed that immune characteristics difference between patients in early stage and advanced stage. Immunohistochemical results confirmed that C1QB, FCER1G, FPR3 and TYROBP were significantly associated with disease progression in GC. Conclusion: Our study identified that C1QB, FCER1G, FPR3 and TYROBP played important roles in the progression of GC, and their specific mechanisms are worth further study.

The histone methyltransferase SUV420H2 regulates brown and beige adipocyte thermogenesis.

Activation of brown adipose tissue (BAT) thermogenesis increases energy expenditure and alleviates obesity. Here we discover that histone methyltransferase suppressor of variegation 4-20 homolog 2 (Suv420h2) expression parallels that of Ucp1 in brown and beige adipocytes and that Suv420h2 knockdown significantly reduces - whereas Suv420h2 overexpression significantly increases - Ucp1 levels in brown adipocytes. Suv420h2 knockout (H2KO) mice exhibit impaired cold-induced thermogenesis and are prone to diet-induced obesity. In contrast, mice with specific overexpression of Suv420h2 in adipocytes display enhanced cold-induced thermogenesis and are resistant to diet-induced obesity. Further study shows that Suv420h2 catalyzes H4K20 trimethylation at eukaryotic translation initiation factor 4E-binding protein 1 (4e-bp1) promoter, leading to downregulated expression of 4e-bp1, a negative regulator of the translation initiation complex. This in turn upregulates PGC1α protein levels, and this upregulation is associated with increased expression of thermogenic program. We conclude that Suv420h2 is a key regulator of brown/beige adipocyte development and thermogenesis.