Machine learning for identifying tumor stemness genes and developing prognostic model in gastric cancer.

Gastric cancer presents a formidable challenge, marked by its debilitating nature and often dire prognosis. Emerging evidence underscores the pivotal role of tumor stem cells in exacerbating treatment resistance and fueling disease recurrence in gastric cancer. Thus, the identification of genes contributing to tumor stemness assumes paramount importance. Employing a comprehensive approach encompassing ssGSEA, WGCNA, and various machine learning algorithms, this study endeavors to delineate tumor stemness key genes (TSKGs). Subsequently, these genes were harnessed to construct a prognostic model, termed the Tumor Stemness Risk Genes Prognostic Model (TSRGPM). Through PCA, Cox regression analysis and ROC curve analysis, the efficacy of Tumor Stemness Risk Scores (TSRS) in stratifying patient risk profiles was underscored, affirming its ability as an independent prognostic indicator. Notably, the TSRS exhibited a significant correlation with lymph node metastasis in gastric cancer. Furthermore, leveraging algorithms such as CIBERSORT to dissect immune infiltration patterns revealed a notable association between TSRS and monocytes and other cell. Subsequent scrutiny of tumor stemness risk genes (TSRGs) culminated in the identification of CDC25A for detailed investigation. Bioinformatics analyses unveil CDC25A's implication in driving the malignant phenotype of tumors, with a discernible impact on cell proliferation and DNA replication in gastric cancer. Noteworthy validation through in vitro experiments corroborated the bioinformatics findings, elucidating the pivotal role of CDC25A expression in modulating tumor stemness in gastric cancer. In summation, the established and validated TSRGPM holds promise in prognostication and delineation of potential therapeutic targets, thus heralding a pivotal stride towards personalized management of this malignancy.

Effects of atmospheric particulate pollution on lung function of athletes.

There is a knowledge gap on how ground-level particulate pollution affects labor productivity in emerging nations due to a lack of study, especially when it comes to outdoor work settings like couriers in the express delivery industry. Combining findings from two research projects, this paper examines the socioeconomic consequences of particulate matter and ground-level particulate pollution. Special panel dataset from China's express delivery companies are used, we study how particulate pollution affects courier productivity. The instrumental variable of our analysis was built by particulate pollution data from upwind towns. Moreover, a comparable rise in particulate levels during the 30 days caused a significant 23.7% decline in worker productivity. This draws attention to a neglected area of the economic effects of particulate pollution, especially in underdeveloped countries. Our results also highlight the wider health hazards connected to outdoor activities in high-pollution locations, drawing comparisons on outdoor exercisers and particulate matter concentrations. The critical need for coordinated policy attention addressing both ground-level Particulate and particle matters in developing nations is highlighted by the increased risk of lung function impairment among outdoor exercisers owing to excessive particulate matter concentrations. The interrelated risks that air pollution poses to public health and economic productivity are clarified by this Comprehensive viewpoint.

The cAMP receptor protein gene contributes to growth, stress resistance, and colonization of Actinobacillus pleuropneumoniae.

Porcine infectious pleuropneumonia (PCP) is a severe disease of porcine caused by Actinobacillus pleuropneumoniae (APP). The spread of PCP remains a threat to the porcine farms and has been known to cause severe economic losses. The cAMP receptor protein (CRP) serves as a pivotal player in helping bacteria adapt to shifts in their environment, particularly when facing the challenges posed by bacterial infections. In this study, we investigated the role of CRP in APP. Our results revealed that crp mutant (Δcrp) strains were more sensitive to acidic and osmotic stress resistance and had lower biofilm formation ability than wild-type (WT) strains. Furthermore, the Δcrp strains showed deficiencies in anti-phagocytosis, adhesion, and invasion upon interaction with host cells. Mice infected with the Δcrp strains demonstrated reduced bacterial loads in their lungs compared to those infected with the WT strains. This study reveals the pivotal role of crp gene expression in regulating pleuropneumonia growth, stress resistance, iron utilization, biofilm formation, phagocytosis, adhesion, invasion and colonization. Our discoveries offer novel perspectives on understanding the development and progression of APP infections.

Uniparental disomy: expanding the clinical and molecular phenotypes of whole chromosomes.

Uniparental disomy (UPD) refers to as both homologous chromosomes inherited from only one parent without identical copies from the other parent. Studies on clinical phenotypes in UPDs are usually focused on the documented UPD 6, 7, 11, 14, 15, and 20, which directly lead to imprinting disorders. This study describes clinical phenotypes and genetic findings of three patients with UPD 2, 9, and 14, respectively. Chromosomal microarray (CMA), UPDtool, methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) and whole-exome sequencing (WES) analysis were performed to characterize the genetic etiology. The CMA revealed a homozygous region involving the whole chromosome 2 and 9, a partial region of homozygosity in chromosome 14. UPD-tool revealed a paternal origin of the UPD2. MS-MLPA showed hypomethylation of imprinting gene MEG3 from maternal origin in the UPD14 case. In addition, UPD14 case displayed complex symptoms including growth failure, hypotonia and acute respiratory distress syndrome (ARDS), accompanied by several gene mutations with heterozygous genotype by WES analysis. Furthermore, we reviewed the documented UPDs and summarized the clinical characteristics and prognosis. This study highlighted the importance to confirm the diagnosis and origin of UPD using genetic testing. Therefore, it is suggested that expanding of the detailed phenotypes and genotypes provide effective guidance for molecule testing and genetic counseling, and promote further biological investigation to the underlying mechanisms of imprinted disorders and accompanied copy number variations.

Construction, Characterization, and Application of an Ammonium Transporter (AmtB) Deletion Mutant of the Nitrogen-Fixing Bacterium Kosakonia radicincitans GXGL-4A in Cucumis sativus L. Seedlings.

Nitrogen is an important factor affecting crop yield, but excessive use of chemical nitrogen fertilizer has caused decline in nitrogen utilization and soil and water pollution. Reducing the utilization of chemical nitrogen fertilizers by biological nitrogen fixation (BNF) is feasible for green production of crops. However, there are few reports on how to have more ammonium produced by nitrogen-fixing bacteria (NFB) flow outside the cell. In the present study, the amtB gene encoding an ammonium transporter (AmtB) in the genome of NFB strain Kosakonia radicincitans GXGL-4A was deleted and the △amtB mutant was characterized. The results showed that deletion of the amtB gene had no influence on the growth of bacterial cells. The extracellular ammonium nitrogen (NH4+) content of the △amtB mutant under nitrogen-free culture conditions was significantly higher than that of the wild-type strain GXGL-4A (WT-GXGL-4A), suggesting disruption of NH4+ transport. Meanwhile, the plant growth-promoting effect in cucumber seedlings was visualized after fertilization using cells of the △amtB mutant. NFB fertilization continuously increased the cucumber rhizosphere soil pH. The nitrate nitrogen (NO3-) content in soil in the △amtB treatment group was significantly higher than that in the WT-GXGL-4A treatment group in the short term but there was no difference in soil NH4+ contents between groups. Soil enzymatic activities varied during a 45-day assessment period, indicating that △amtB fertilization influenced soil nitrogen cycling in the cucumber rhizosphere. The results will provide a solid foundation for developing the NFB GXGL-4A into an efficient biofertilizer agent.

The interaction of persistent antiphospholipid antibodies positivity and cigarette smoking is associated with an increased risk of cardiovascular events: Cross-sectional and longitudinal analysis.

BACKGROUND: The antiphospholipid antibody (aPL)-positivity was suggested as a nontraditional risk of coronary artery disease (CAD) and it was associated with cigarette smoking. The co-occurrence of them was usually reported in individuals with cardiovascular diseases. This study was to demonstrate their interaction on the increasing risk of cardiovascular events. METHODS AND RESULTS: A total of 826 consecutive male individuals who underwent coronary angiography (CAG) /percutaneous coronary intervention (PCI) were prospectively followed and classified into three groups based on different smoking statuses. The current smoking subjects had the highest occurrence of aPL-positivity, including aCL IgM (20.1%) and aß2GP1 IgM (15.5%). IgM isotype positivity was an independent risk factor of CAD in the multivariate model, OR: 2.70 (1.52-4.80) for aCL IgM and OR:2.50 (1.35-4.63) for aß2GP1 IgM.The interaction of current smoking and IgM isotype positivity was significantly associated with increased risk of CAD, OR: 8.75(4.59-16.66) for aCL IgM and OR: 8.78(4.28-17.98) for aß2GP1 IgM. During about 3 years of follow-up, the smoking patients carrying persistent aPL positivity had the highest cumulative incidence of recurrent myocardial infarction and in-stent restenosis after CAD. CONCLUSION: The interaction of current smoking and IgM isotype positivity was significantly associated with the increased risk of CAD, including positive aCL IgM and aß2GP1 IgM. Cigarette smoking elevated the risk of subsequent cardiovascular events in the presence of IgM isotype positivity, including recurrent myocardial infarction and in-stent restenosis.

Comparison of COVID-19 and seasonal influenza under different intensities of non-pharmaceutical interventions and vaccine effectiveness.

Background: The COVID-19 pandemic has lasted more than 2 years, and the global epidemic prevention and control situation remains challenging. Scientific decision-making is of great significance to people's production and life as well as the effectiveness of epidemic prevention and control. Therefore, it is all the more important to explore its patterns and put forward countermeasures for the pandemic of respiratory infections. Methods: Modeling of epidemiological characteristics was conducted based on COVID-19 and influenza characteristics using improved transmission dynamics models to simulate the number of COVID-19 and influenza infections in different scenarios in a hypothetical city of 100,000 people. By comparing the infections of COVID-19 and influenza in different scenarios, the impact of the effectiveness of vaccination and non-pharmaceutical interventions (NPIs) on disease trends can be calculated. We have divided the NPIs into three levels according to the degree of restriction on social activities (including entertainment venues, conventions, offices, restaurants, public transport, etc.), with social controls becoming progressively stricter from level 1 to level 3. Results: In the simulated scenario where susceptible individuals were vaccinated with three doses of COVID-19 coronaVac vaccine, the peak number of severe cases was 26.57% lower than that in the unvaccinated scenario, and the peak number of infection cases was reduced by 10.16%. In the scenario with level three NPIs, the peak number of severe cases was reduced by 7.79% and 15.43%, and the peak number of infection cases was reduced by 12.67% and 28.28%, respectively, compared with the scenarios with NPIs intensity of level 2 and level 1. For the influenza, the peak number of severe cases in the scenario where the entire population were vaccinated was 89.85%, lower than that in the unvaccinated scenario, and the peak number of infections dropped by 79.89%. Conclusion: The effectiveness of COVID-19 coronaVac vaccine for preventing severe outcomes is better than preventing infection; for the prevention and control of influenza, we recommend influenza vaccination as a priority over strict NPIs in the long term.

Siderophore Synthesis Ability of the Nitrogen-Fixing Bacterium (NFB) GXGL-4A is Regulated at the Transcriptional Level by a Transcriptional Factor (trX) and an Aminomethyltransferase-Encoding Gene (amt).

Kosakonia radicincitans GXGL-4A, a gram-negative nitrogen-fixing (NF) bacterial strain is coated with a thick capsulatus on the surface of cell wall, which becomes a physical barrier for exogenous DNA to enter the cell, so the operation of genetic transformation is difficult. In this study, an optimized Tn5 transposon mutagenesis system was established by using a high osmotic HO-1 medium combined with the electroporation transformation. Eventually, a mutant library containing a total of 1633 Tn5 insertional mutants were established. Of these mutants, the mutants M81 and M107 were found to have an enhanced capability to synthesize siderophore through the CAS agar plate assay and the spectrophotometric determination. The bacterial cells of two mutants were applied in cucumber growth-promoting experiment. Cucumber seedlings treated with M81 and M107 cells had a significant increase in biomass including seedling height, seedling fresh weight, root fresh weight, and root length. The whole genome sequencing of the mutants M81 and M107 showed that the integration sites of Tn5 transposon element were located in MmyB-like helix-turn-helix transcription regulator (locus tag: A3780_19720, trX) and aminomethyltransferase-encoding genes (locus tag: A3780_01680, amt) in the genome of GXGL-4A, respectively. The ability of siderophore synthesis of the target mutants was improved by Tn5 insertion mutagenesis, and the mutants obtained showed a good plant growth-promoting effect when applied to the cucumber seedlings. The results suggest that the identified functional genes regulates the biosynthesis of siderophore in azotobacter GXGL-4A, and the specific mechanism needs to be further investigated.

The Significance of NLRP Inflammasome in Neuropsychiatric Disorders.

The NLRP inflammasome is a multi-protein complex which mainly consists of the nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain. Its activation is linked to microglial-mediated neuroinflammation and partial neuronal degeneration. Many neuropsychiatric illnesses have increased inflammatory responses as both a primary cause and a defining feature. The NLRP inflammasome inhibition delays the progression and alleviates the deteriorating effects of neuroinflammation on several neuropsychiatric disorders. Evidence on the central effects of the NLRP inflammasome potentially provides the scientific base of a promising drug target for the treatment of neuropsychiatric disorders. This review elucidates the classification, composition, and functions of the NLRP inflammasomes. It also explores the underlying mechanisms of NLRP inflammasome activation and its divergent role in neuropsychiatric disorders, including Alzheimer's disease, Huntington's disease, Parkinson's disease, depression, drug use disorders, and anxiety. Furthermore, we explore the treatment potential of the NLRP inflammasome inhibitors against these disorders.

Modeling and Predicting Pulmonary Tuberculosis Incidence and Its Association with Air Pollution and Meteorological Factors Using an ARIMAX Model: An Ecological Study in Ningbo of China.

The autoregressive integrated moving average with exogenous regressors (ARIMAX) modeling studies of pulmonary tuberculosis (PTB) are still rare. This study aims to explore whether incorporating air pollution and meteorological factors can improve the performance of a time series model in predicting PTB. We collected the monthly incidence of PTB, records of six air pollutants and six meteorological factors in Ningbo of China from January 2015 to December 2019. Then, we constructed the ARIMA, univariate ARIMAX, and multivariate ARIMAX models. The ARIMAX model incorporated ambient factors, while the ARIMA model did not. After prewhitening, the cross-correlation analysis showed that PTB incidence was related to air pollution and meteorological factors with a lag effect. Air pollution and meteorological factors also had a correlation. We found that the multivariate ARIMAX model incorporating both the ozone with 0-month lag and the atmospheric pressure with 11-month lag had the best performance for predicting the incidence of PTB in 2019, with the lowest fitted mean absolute percentage error (MAPE) of 2.9097% and test MAPE of 9.2643%. However, ARIMAX has limited improvement in prediction accuracy compared with the ARIMA model. Our study also suggests the role of protecting the environment and reducing pollutants in controlling PTB and other infectious diseases.

Reactive oxygen species-induced SIAH1 promotes granulosa cells' senescence in premature ovarian failure.

Reactive oxygen species (ROS) exposure triggers granulosa cells' (GCs) senescence, which is an important causal factor for premature ovarian failure (POF). However, underlying mechanism in this process remains unknown. In our study, we observed increased ROS levels in POF ovarian tissues, POF patient follicular GCs and cyclophosphamide (CTX) pretreated GCs. Correspondingly, increased SIAH1, reduced TRF2 and GC senescence were also found in these cases. Silencing of SIAH1 rescued ROS-induced TRF2 reduction and cell senescence in GCs. Moreover, SIAH1 co-localized with TRF2 in the cytoplasm, facilitating its ubiquitination degradation, further leading to telomere abnormalities in GCs. In conclusion, our findings indicate that ROS induces telomere abnormalities by augmenting SIAH1-mediated TRF2 degradation, leading to cell senescence in GCs in POF processing.

SODAR: Segmenting Objects by Dynamically Aggregating Neighboring Mask Representations.

Recent state-of-the-art one-stage instance segmentation model SOLO divides the input image into a grid and directly predicts per grid cell object masks with fully-convolutional networks, yielding comparably good performance as traditional two-stage Mask R-CNN yet enjoying much simpler architecture and higher efficiency. We observe SOLO generates similar masks for an object at nearby grid cells, and these neighboring predictions can complement each other as some may better segment certain object part, most of which are however directly discarded by non-maximum-suppression. Motivated by the observed gap, we develop a novel learning-based aggregation method that improves upon SOLO by leveraging the rich neighboring information while maintaining the architectural efficiency. The resulting model is named SODAR. Unlike the original per grid cell object masks, SODAR is implicitly supervised to learn mask representations that encode geometric structure of nearby objects and complement adjacent representations with context. The aggregation method further includes two novel designs: 1) a mask interpolation mechanism that enables the model to generate much fewer mask representations by sharing neighboring representations among nearby grid cells, and thus saves computation and memory; 2) a deformable neighbour sampling mechanism that allows the model to adaptively adjust neighbor sampling locations thus gathering mask representations with more relevant context and achieving higher performance. SODAR significantly improves the instance segmentation performance, e.g., it outperforms a SOLO model with ResNet-101 backbone by 2.2 AP on COCO test set, with only about 3% additional computation. We further show consistent performance gain with the SOLOv2 model.

Adversarial Domain Adaptation With Prototype-Based Normalized Output Conditioner.

Domain adversarial training has become a prevailing and effective paradigm for unsupervised domain adaptation (UDA). To successfully align the multi-modal data structures across domains, the following works exploit discriminative information in the adversarial training process, e.g., using multiple class-wise discriminators and involving conditional information in the input or output of the domain discriminator. However, these methods either require non-trivial model designs or are inefficient for UDA tasks. In this work, we attempt to address this dilemma by devising simple and compact conditional domain adversarial training methods. We first revisit the simple concatenation conditioning strategy where features are concatenated with output predictions as the input of the discriminator. We find the concatenation strategy suffers from the weak conditioning strength. We further demonstrate that enlarging the norm of concatenated predictions can effectively energize the conditional domain alignment. Thus we improve concatenation conditioning by normalizing the output predictions to have the same norm of features, and term the derived method as Normalized OutpUt coNditioner (NOUN). However, conditioning on raw output predictions for domain alignment, NOUN suffers from inaccurate predictions of the target domain. To this end, we propose to condition the cross-domain feature alignment in the prototype space rather than in the output space. Combining the novel prototype-based conditioning with NOUN, we term the enhanced method as PROtotype-based Normalized OutpUt coNditioner (PRONOUN). Experiments on both object recognition and semantic segmentation show that NOUN can effectively align the multi-modal structures across domains and even outperform state-of-the-art domain adversarial training methods. Together with prototype-based conditioning, PRONOUN further improves the adaptation performance over NOUN on multiple object recognition benchmarks for UDA. Code is available at https://github.com/tim-learn/NOUN.

Screening for Candidate Genes Associated with Biocontrol Mechanisms of Bacillus pumilus DX01 Using Tn5 Transposon Mutagenesis and a 2-DE-Based Comparative Proteomic Analysis.

A total of 1467 mutants of the biocontrol bacterium Bacillus pumilus DX01 were obtained by Tn5 insertional mutagenesis and subjected to the determination of antagonistic capabilities. Compared with the wild-type strain DX01, the mutant M25 was identified to have the most significant reduction in antagonistic capability against the phytopathogen Bipolaris maydis and extracellular proteinase activity. The integration site of the exogenous T-DNA in the genome of mutant M25 was revealed in the coding region of malony CoA-ACP transacylase (MCAT) gene (mcat), which belongs to a polyketide synthase (PKS) gene cluster, DX01pks of B. pumilus DX01. Furthermore, the whole DX01pks gene cluster was cloned using Illumina Solexa sequencing technology, and it has a modular framework different from the other two gene clusters involved in polyketide synthesis in B. amyloliquefaciens FZB42 (pks1) and B. subtilis 168 (pksX). Finally, in order to gain more insights into the molecular mechanisms of biocontrol of B. pumilus DX01, the changes in the relative level of expression of total proteins between the original strain DX01 and the mutant M25 were detected by 2-DE-based proteomic analysis. A total of twenty differentially expressed proteins were identified upon the mcat gene transposition mutagenesis. Of these proteins, seven proteins were up-regulated in expression level and the other proteins were down-regulated. Taken together, the results in this study showed that Tn5 transposon mutagenesis of B. pumilus DX01 can lead to a significant change of antiphytopathogen ability, and the DX01pks gene cluster possibly play a potential role in the biocontrol processes of this bacterium.

Gcluster: a simple-to-use tool for visualizing and comparing genome contexts for numerous genomes.

MOTIVATION: Comparing the organization of gene, gene clusters and their flanking genomic contexts is of critical importance to the determination of gene function and evolutionary basis of microbial traits. Currently, user-friendly and flexible tools enabling to visualize and compare genomic contexts for numerous genomes are still missing. RESULTS: We here present Gcluster, a stand-alone Perl tool that allows researchers to customize and create high-quality linear maps of the genomic region around the genes of interest across large numbers of completed and draft genomes. Importantly, Gcluster integrates homologous gene analysis, in the form of a built-in orthoMCL, and mapping genomes onto a given phylogeny to provide superior comparison of gene contexts. AVAILABILITY AND IMPLEMENTATION: Gcluster is written in Perl and released under GPLv3. The source code is freely available at https://github.com/Xiangyang1984/Gcluster and http://www.microbialgenomic.com/Gcluster_tool.html. Gcluster can also be installed through conda: 'conda install -c bioconda gcluster'. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Complete Genome Sequence of Kosakonia radicincitans GXGL-4A, a Nitrogen-Fixing Bacterium with Capability to Degrade TEX.

Kosakonia radicincitans GXGL-4A, a free-living nitrogen-fixing (NF) bacterial strain isolated from maize (Zea mays L.) roots was found to have ability to degrade aromatic hydrocarbons. In this study, we describe the main morphological characteristics of bacterium, aromatic hydrocarbon-degrading capability, and the complete genome of K. radicincitans GXGL-4A. The genome is consisted of only one 5,687,681 bp linear chromosome with a G + C content of 53.96%. The strain has two genetically distinct nitrogenase systems, one based on molybdenum (Mo) similar to nitrogenase isolated from a wide range of nitrogen-fixing organisms, and the other contains iron (Fe). The differences in transcriptional level of several important nitrogen fixation (nif) genes between LB (nitrogen-rich, NR) and A15 nitrogen-free (nitrogen-limited, NL) culture conditions were detected using Real-time Quantitative Reverse Transcription PCR (qRT-PCR). The bacterial cells of GXGL-4A can grow well in LB liquid medium containing 1% toluene, ethylbenzene or xylene, suggesting a good resistance to the tested aromatic hydrocarbons. The results of GC-MS analysis showed that K. radicincitans GXGL-4A has a good capability to degrade toluene, ethylbenzene, and xylene (TEX). Completion of the genome sequencing will no doubt contribute to the deep exploration and comprehensive utilization of this NF bacterium in sustainable agriculture and bioremediation of aromatic pollutants.

Impact of short-term application of seaweed fertilizer on bacterial diversity and community structure, soil nitrogen contents, and plant growth in maize rhizosphere soil.

The effects of the short-term application of Ascophyllum nodosum-fermented seaweed fertilizer on the bacterial community, soil nitrogen contents, and plant growth in maize rhizosphere soil were evaluated. The changes in the bacterial community composition and nitrogen contents including those of total nitrogen (TN), nitrate nitrogen (NO3--N) and ammonium nitrogen (NH4+-N) in rhizosphere soils in response to treatment with seaweed fertilizer were determined. Furthermore, soil enzymatic activity and crop biomass were analyzed. The relative abundance of the dominant phyla varied regularly with fertilization, and bacterial α-diversity was apparently influenced by seaweed fertilizer amendment. The TN contents of all soil samples decreased gradually, and the NO3--N and NH4+-N contents of the soils treated with seaweed fertilizer were much higher than those of the control soils. Similarly, the enzymatic activities of dehydrogenase, nitrite reductase, urease, and cellulase in the soil were significantly increased on day 3, day 8, and day 13 after the application of seaweed fertilizer to the maize rhizosphere soil. However, there was no difference in the activity of soil sucrase between the treatment group and the control group. In this study, the growth of maize seedlings was confirmed to be greatly promoted by the utilization of seaweed fertilizer. These results deepen our understanding of plant-microbe interactions in agroecosystems and should benefit the wide use of seaweed fertilizer in sustainable agricultural production.

Effect of solvent environment on excited state intramolecular proton transfer in 2-(4-(dimethylamino)phenyl)-3-hydroxy-6,7-dimethoxy-4h-chromen-4-one.

The new ratiometric fluorescent probe 2-(4-(dimethylamino)phenyl)-3-hydroxy-6,7-dimethoxy-4h-chromen-4-one (HOF) monitoring of methanol in biodiesel was discovered experimentally (T. Y. Qin et al., Sens. Actuators, B, 2018, 277, 484-491). But the experimental study did not report the reaction mechanism in detail. In this study, density functional theory (DFT) and time-density functional theory (TDDFT) methods were used to theoretically study the excited-state intramolecular proton transfer (ESIPT) process of the HOF molecule. The molecular structure in the ground state and the excited state was optimized, and the infrared vibrational spectra, the frontier molecular orbitals, the charge transfer, the potential energy curves and the transition-state structures were calculated. The calculated results prove that the solvent polarity has a great influence on the ESIPT reaction of the HOF molecule. As the solvent polarity increased, the intensity of the intramolecular hydrogen bond decreased, and ESIPT was more difficult to occur. This work has studied the mechanism of the ESIPT reaction in more detail, and paved the way for future research on HOF molecules.

Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition.

Considering the lack of precision in transforming measured micro-electro-mechanical system (MEMS) accelerometer output signals into elevation signals, this paper proposes a bridge dynamic displacement reconstruction method based on the combination of ensemble empirical mode decomposition (EEMD) and time domain integration, according to the vibration signal traits of a bridge. Through simulating bridge analog signals and verifying a vibration test bench, four bridge dynamic displacement monitoring methods were analyzed and compared. The proposed method can effectively eliminate the influence of low-frequency integral drift and high-frequency ambient noise on the integration process. Furthermore, this algorithm has better adaptability and robustness. The effectiveness of the method was verified by field experiments on highway elevated bridges.

Preparation and Specific Capacitance Properties of Sulfur, Nitrogen Co-Doped Graphene Quantum Dots.

Sulfur, nitrogen co-doped graphene quantum dots (S, N-GQDs) with high crystallinity were obtained by a top-down strategy. The as-prepared S, N-GQDs were investigated and the results indicate that S, N-GQDs exhibit a transverse dimension about 20 nm and a topographic height of 1-2 layers graphene. The incorporation of S, N can effectively reduce the layers of GQDs and strip the graphene sheets. Moreover, the S, N-GQDs reveal an absorption band located at 405 nm and exhibit an adjustable fluorescence characteristic in the excitation-visible range. Meanwhile, the S, N-GQDs shows a high specific capacitance of 362.60 F g-1 at a fixed scan rate of 5 mV s -1. This high performance is ascribed to the additional high pseudocapacitance provided by the doped S, N and the doping state acting as a trap state to enhance the charge storage capacity. The high specific capacitance advantages of S, N-GQDs illustrate their potential prospects in the capacitors.