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Groundwater, a fundamental asset, isn't effectively accessible in some parts of the world. The current research work pointed toward obtaining precise maps of potential groundwater zones. This study aimed for potential groundwater modeling and extracting the precise maps using four new advanced hybrid ML models (Dagging-HP, Bagging-HP, AdaBoost-HP, Decorate-HP) and one single model Hyperpipes (HP) in the Doji Watershed, situated in the eastern part of Golestan province, Iran. Among the selected models, the AdaBoost-HP model is the most efficient, with an AUC - ROC of 0.972, accuracy (0.922), sensitivity (0.906), and specificity (0.938), which gives the most promising values, when determining the collinearity between the 14 training factors, which are, in descending order of significance, LULC, Distance to stream (DtS), Topography wetness index (TWI), HAND, Distance to the road (DtR), Geomorphology, Topography position index (TPI), Lithology, Drainage density (DD), Elevation, Slope, Rainfall, and Clay (%). The AUC-ROC approach was employed to assess the model's performance along with Accuracy, Specificity, and Sensitivity. This model revealed that 7.37% has very high groundwater potential in the eastern and south-western parts of the study, whereas 36.8% has a very low groundwater potential in the north-western and south-eastern parts of the study. It can be said from this assessment that results obtained from this investigation are better and more reliable, which gives essential encouragement for further study put on this method for groundwater potential mapping of other areas of the world along with other areas of hydrogeological investigations. [ABSTRACT FROM AUTHOR]

The risk of cholangitis after ERCP implantation in malignant obstructive jaundice patients remains unknown. To develop models based on artificial intelligence methods to predict cholangitis risk more accurately, according to patients after stent implantation in patients' MOJ clinical data. This retrospective study included 218 patients with MOJ undergoing ERCP surgery. A total of 27 clinical variables were collected as input variables. Seven models (including univariate analysis and six machine learning models) were trained and tested for classified prediction. The model' performance was measured by AUROC. The RFT model demonstrated excellent performances with accuracies up to 0.86 and AUROC up to 0.87. Feature selection in RF and SHAP was similar, and the choice of the best variable subset produced a high performance with an AUROC up to 0.89. We have developed a hybrid machine learning model with better predictive performance than traditional LR prediction models, as well as other machine learning models for cholangitis based on simple clinical data. The model can assist doctors in clinical diagnosis, adopt reasonable treatment plans, and improve the survival rate of patients. [ABSTRACT FROM AUTHOR]

Background: Numerous studies highlight the genetic underpinnings of mental disorders comorbidity, particularly in anxiety, depression, and schizophrenia. However, their shared genetic loci are not well understood. Our study employs Mendelian randomization (MR) and colocalization analyses, alongside multi-omics data, to uncover potential genetic targets for these conditions, thereby informing therapeutic and drug development strategies. Methods: We utilized the Consortium for Linkage Disequilibrium Score Regression (LDSC) and Mendelian Randomization (MR) analysis to investigate genetic correlations among anxiety, depression, and schizophrenia. Utilizing GTEx V8 eQTL and deCODE Genetics pQTL data, we performed a three-step summary-data-based Mendelian randomization (SMR) and protein–protein interaction analysis. This helped assess causal and comorbid loci for these disorders and determine if identified loci share coincidental variations with psychiatric diseases. Additionally, phenome-wide association studies, drug prediction, and molecular docking validated potential drug targets. Results: We found genetic correlations between anxiety, depression, and schizophrenia, and under a meta-analysis of MR from multiple databases, the causal relationships among these disorders are supported. Based on this, three-step SMR and colocalization analyses identified ITIH3 and CCS as being related to the risk of developing depression, while CTSS and DNPH1 are related to the onset of schizophrenia. BTN3A1, PSMB4, and TIMP4 were identified as comorbidity loci for both disorders. Molecules that could not be determined through colocalization analysis were also presented. Drug prediction and molecular docking showed that some drugs and proteins have good binding affinity and available structural data. Conclusions: Our study indicates genetic correlations and shared risk loci between anxiety, depression, and schizophrenia. These findings offer insights into the underlying mechanisms of their comorbidities and aid in drug development. [ABSTRACT FROM AUTHOR]

Herein, we designed a metal-coordinated carrier-free nanodrug (USFe3+LA NPs) with near sphere shape by co-assembling of UA, SRF, Fe3+, low molecular weight protamine (LMWP), and epithelial cell adhesion molecule (EpCAM) aptamer via a facile self-assembly method to improve the efficacy of chemotherapy monotherapy and achieve synergistic therapy. USFe3+LA NPs could inhibit tumor metastasis by inhibiting the intercellular adhesion molecule-1 (ICAM-1) and vascular endothelial growth factor (VEGF) expression. In addition, USFe3+LA NPs could enhance immune response and sensitize tumors to immune checkpoint inhibitors PD-L1 antibody. It was demonstrated that USFe3+LA NPs significantly inhibited tumor growth and metastasis, showing that this nano-delivery system synergistically enhanced its anti-tumor effect. These nanodrugs will provide a new strategy for combined chemotherapy, CDT, ferroptosis, and immunotherapy. [Display omitted] The heterogeneity of hepatocellular carcinoma (HCC) and the complexity of the tumor microenvironment (TME) pose challenges to efficient drug delivery and the antitumor efficacy of combined or synergistic therapies. Herein, a metal-coordinated carrier-free nanodrug (named as USFe3+ LA NPs) was developed for ferroptosis-mediated multimodal synergistic anti-HCC. Natural product ursolic acid (UA) was incorporated to enhance the sensitivity of tumor cells to sorafenib (SRF). Surface decoration of cell penetration peptide and epithelial cell adhesion molecule aptamer facilitated the uptake of USFe3+ LA NPs by HepG2 cells. Meanwhile, Fe3+ ions could react with intracellular hydrogen peroxide, generating toxic hydroxyl radical (·OH) for chemodynamical therapy (CDT) and amplified ferroptosis by cystine/glutamate antiporter system (System X c −), which promoted the consumption of glutathione (GSH) and inhibited the expression of glutathione peroxidase 4 (GPX4). Notably, these all-in-one nanodrugs could inhibit tumor metastasis and induced immunogenic cell death (ICD). Last but not least, the nanodrugs demonstrated favorable biocompatibility, augmenting the immune response against the programmed death-ligand 1 (PD-L1) by increasing cytotoxic T cell infiltration. In vivo studies revealed significant suppression of tumor growth and distant metastasis. Overall, our work introduced a novel strategy for applications of metal-coordinated co-assembled carrier-free nano-delivery system in HCC combination therapy, especially in the realms of cancer metastasis prevention and immunotherapy. [ABSTRACT FROM AUTHOR]

Adaptive cruise control (ACC) enables efficient, safe, and intelligent vehicle control by autonomously adjusting speed and ensuring a safe following distance from the vehicle in front. This paper proposes a novel adaptive cruise system, namely the Safety-First Reinforcement Learning Adaptive Cruise Control (SFRL-ACC). This system aims to leverage the model-free nature and high real-time inference efficiency of Deep Reinforcement Learning (DRL) to overcome the challenges of modeling difficulties and lower computational efficiency faced by current optimization control-based ACC methods while simultaneously maintaining safety advantages and optimizing ride comfort. Firstly, we transform the ACC problem into a safe DRL formulation Constrained Markov Decision Process (CMDP) by carefully designing state, action, reward, and cost functions. Subsequently, we propose the Projected Constrained Policy Optimization (PCPO)-based ACC Algorithm SFRL-ACC, which is specifically tailored to solve the CMDP problem. PCPO incorporates safety constraints that further restrict the trust region formed by the Kullback–Leibler (KL) divergence, facilitating DRL policy updates that maximize performance while keeping safety costs within their limit bounds. Finally, we train an SFRL-ACC policy and compare its computation time, traffic efficiency, ride comfort, and safety with state-of-the-art MPC-based ACC control methods. The experimental results prove the superiority of the proposed method in the aforementioned performance aspects. [ABSTRACT FROM AUTHOR]

Amorphous alloys or metallic glasses (MGs) thin films have attracted extensive attention in various fields due to their unique functional properties. Here, we use in situ heating transmission electron microscopy (TEM) to investigate the thermal stability and crystallization behavior of Pd-Au-Si thin films prepared by a pulsed laser deposition (PLD) method. Upon heating treatment inside a TEM, we trace the structural changes in the Pd-Au-Si thin films through directly recording high-resolution images and diffraction patterns at different temperatures. TEM observations reveal that the Pd-Au-Si thin films started to nucleate with small crystalline embryos uniformly distributed in the glassy matrix upon approaching the glass transition temperature T g = 625 K , and subsequently, the growth of crystalline nuclei into sub-10 nm Pd-Si nanocrystals commenced. Upon further increasing the temperature to 673 K , the thin films transformed to micro-sized patches of stacking-faulty lamellae that further crystallized into Pd 9 Si 2 and Pd 3 Si intermetallic compounds. Interestingly, with prolonged thermal heating at elevated temperatures, the Pd 9 Si 2 transformed to Pd 3 Si . Simultaneously, the solute Au atoms initially dissolved in glassy alloys and eventually precipitated out of the Pd 9 Si 2 and Pd 3 Si intermetallics, forming nearly spherical Au nanocrystals. Our TEM results reveal the unique thermal stability and crystallization processes of the PLD-prepared Pd-Au-Si thin films as well as demonstrate a possibility of producing a large quantity of pure nanocrystals out of amorphous solids for various applications. [ABSTRACT FROM AUTHOR]

Summary Gene expression is regulated at multiple levels, including RNA processing and DNA methylation/demethylation. How these regulations are controlled remains unclear. Here, through analysis of a suppressor for the OsEIN2 over‐expressor, we identified an RNA recognition motif protein SUPPRESSOR OF EIN2 (SOE). SOE is localized in nuclear speckles and interacts with several components of the spliceosome. We find SOE associates with hundreds of targets and directly binds to a DNA glycosylase gene DNG701 pre‐mRNA for efficient splicing and stabilization, allowing for subsequent DNG701‐mediated DNA demethylation of the transgene promoter for proper gene expression. The V81M substitution in the suppressor mutant protein mSOE impaired its protein stability and binding activity to DNG701 pre‐mRNA, leading to transgene silencing. SOE mutation enhances grain size and yield. Haplotype analysis in c. 3000 rice accessions reveals that the haplotype 1 (Hap 1) promoter is associated with high 1000‐grain weight, and most of the japonica accessions, but not indica ones, have the Hap 1 elite allele. Our study discovers a novel mechanism for the regulation of gene expression and provides an elite allele for the promotion of yield potentials in rice. [ABSTRACT FROM AUTHOR]

Trichoderma spp. are globally distributed and are considered significant fungal resources. This study presents the discovery of 11 new species of Trichoderma: T. caeruleum, T. gongcheniae, T. graminicola, T. graminis, T. hongkuii, T. parapeberdyi, T. neoguizhouense, T. neohongkuii, T. parahamatum, T. parahongkuii, and T. shaanxiensis. All of these new species were isolated from soils, except for T. caeruleum, T. graminicola, T. graminis, and T. neohongkuii, which were found as endophytes in Poaceae plants. The phylogenetic position of these novel species was determined by analysing the concatenated sequences of the second largest nuclear RNA polymerase subunit encoding gene (rpb2) and the translation elongation factor 1-alpha encoding gene (tef1). The results of the phylogenetic analysis revealed that each new species formed a distinct lineage: T. gongcheniae, T. graminicola, T. graminis, T. neoguizhouense, T. parapeberdyi, and T. shaanxiensis belong to the Harzianum Clade, T. hongkuii, T. parahongkuii, and T. neohongkuii are new members of the Koningii Clade, T. parahamatum belongs to the Hamatum Clade, and T. caeruleum does not fall within any of the named clades. The study also provided a detailed description of the morphology and cultural characteristics of the newly discovered Trichoderma species. The discovery contributes to the advancement of knowledge about Trichoderma species resources in China. [ABSTRACT FROM AUTHOR]

In the context of human‐induced warming climate, the atmosphere is expected to hold a greater amount of water vapor, leading to heavier precipitation on a global scale. However, the extent to which changes in extreme rainfall can be attributed to human influences varies at regional scales. Here we conduct attribution analyses on 40 extreme precipitation events in different seasons during 1998–2018 over the Pearl River Delta (PRD), by using the Weather Research and Forecasting (WRF) model and applying the pseudo global warming (PGW) method. The model was integrated with the factual and counterfactual conditions separately, with the latter derived from differences between the Coupled Model Intercomparison Project Phase 5 (CMIP5) historical and historical‐natural runs. By comparing parallel experiments, extreme daily rainfall (>95th percentile) in PRD enhanced by 8%–9.5% for 0.9–1.1 K near‐surface warming (nearly Clausius‐Clapeyron, or CC scaling) in the May‐to‐September (MJJAS) and 12.4% at most for 0.6–0.8 K warming (∼2 × CC rate) in non‐MJJAS seasons; the probability of those extremes increased by 10%–30% during MJJAS (20%–40% in other seasons). While moisture‐related thermodynamic effects play a similar role in modulating rainfall, the wind circulation‐related dynamic effects act differently in different seasons. Changes in MJJAS extremes are related to stronger low‐level southerly winds, while non‐MJJAS rainfall is exacerbated by strengthened low‐level wind convergence and updrafts. Moisture budget analysis suggests that thermodynamic effects associated with the increased moisture amount account for the mean rainfall increase, whereas dynamic effects related to wind circulation changes are responsible for extreme precipitation, regardless of seasons. Key Points: Anthropogenic influences lead to around 20% or more increase in frequency of extreme rainfall events over the Pearl River Delta regionVery extreme rainfall in non‐rainy season tends to become more frequent and stronger than in rainy season under anthropogenic warmingBoth precipitable water and vertical motion have positive contributions to human‐induced increase in 95th percentile rainfall intensity [ABSTRACT FROM AUTHOR]

Nitrite-oxidizing bacteria (NOB) are important nitrifiers whose activity regulates the availability of nitrite and dictates the magnitude of nitrogen loss in ecosystems. In oxic marine sediments, ammonia-oxidizing archaea (AOA) and NOB together catalyze the oxidation of ammonium to nitrate, but the abundance ratios of AOA to canonical NOB in some cores are significantly higher than the theoretical ratio range predicted from physiological traits of AOA and NOB characterized under realistic ocean conditions, indicating that some NOBs are yet to be discovered. Here we report a bacterial phylum Candidatus Nitrosediminicolota, members of which are more abundant than canonical NOBs and are widespread across global oligotrophic sediments. Ca. Nitrosediminicolota members have the functional potential to oxidize nitrite, in addition to other accessory functions such as urea hydrolysis and thiosulfate reduction. While one recovered species (Ca. Nitrosediminicola aerophilus) is generally confined within the oxic zone, another (Ca. Nitrosediminicola anaerotolerans) additionally appears in anoxic sediments. Counting Ca. Nitrosediminicolota as a nitrite-oxidizer helps to resolve the apparent abundance imbalance between AOA and NOB in oxic marine sediments, and thus its activity may exert controls on the nitrite budget.A novel phylum of bacteria widespread in oligotrophic marine sediments are capable of oxidizing nitrite to nitrate and could resolve the apparent abundance mismatch between ammonia- and nitrite-oxidizers. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence, the ability to capture the background characteristics of hyperspectral imagery (HSI) has improved, showing promising performance in hyperspectral anomaly detection (HAD) tasks. However, existing methods proposed in recent years still suffer from certain limitations: (1) Constraints are lacking in the deep feature learning process in terms of the issue of the absence of prior background and anomaly information. (2) Hyperspectral anomaly detectors with traditional self-supervised deep learning methods fail to ensure prioritized reconstruction of the background. (3) The architecture of fully connected deep networks in hyperspectral anomaly detectors leads to low utilization of spatial information and the destruction of the original spatial relationship in hyperspectral imagery and disregards the spectral correlation between adjacent pixels. (4) Hypotheses or assumptions for background and anomaly distributions restrict the performance of many hyperspectral anomaly detectors because the distributions of background land covers are usually complex and not assumable in real-world hyperspectral imagery. In consideration of the above problems, in this paper, we propose a novel fully convolutional auto-encoder based on dual clustering and latent feature adversarial consistency (FCAE-DCAC) for HAD, which is carried out with self-supervised learning-based processing. Firstly, density-based spatial clustering of applications with a noise algorithm and connected component analysis are utilized for successive spectral and spatial clustering to obtain more precise prior background and anomaly information, which facilitates the separation between background and anomaly samples during the training of our method. Subsequently, a novel fully convolutional auto-encoder (FCAE) integrated with a spatial–spectral joint attention (SSJA) mechanism is proposed to enhance the utilization of spatial information and augment feature expression. In addition, a latent feature adversarial consistency network with the ability to learn actual background distribution in hyperspectral imagery is proposed to achieve pure background reconstruction. Finally, a triplet loss is introduced to enhance the separability between background and anomaly, and the reconstruction residual serves as the anomaly detection result. We evaluate the proposed method based on seven groups of real-world hyperspectral datasets, and the experimental results confirm the effectiveness and superior performance of the proposed method versus nine state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The transcription of glycine-rich RNA-binding protein 2 (PeGRP2) transiently increased in the roots and shoots of Populus euphratica (a salt-resistant poplar) upon initial salt exposure and tended to decrease after long-term NaCl stress (100 mM, 12 days). PeGRP2 overexpression in the hybrid Populus tremula × P. alba '717-1B4' (P. × canescens) increased its salt sensitivity, which was reflected in the plant's growth and photosynthesis. PeGRP2 contains a conserved RNA recognition motif domain at the N-terminus, and RNA affinity purification (RAP) sequencing was developed to enrich the target mRNAs that physically interacted with PeGRP2 in P. × canescens. RAP sequencing combined with RT-qPCR revealed that NaCl decreased the transcripts of PeGRP2-interacting mRNAs encoding photosynthetic proteins, antioxidative enzymes, ATPases, and Na+/H+ antiporters in this transgenic poplar. Specifically, PeGRP2 negatively affected the stability of the target mRNAs encoding the photosynthetic proteins PETC and RBCMT; antioxidant enzymes SOD[Mn], CDSP32, and CYB1-2; ATPases AHA11, ACA8, and ACA9; and the Na+/H+ antiporter NHA1. This resulted in (i) a greater reduction in Fv/Fm, YII, ETR, and Pn; (ii) less pronounced activation of antioxidative enzymes; and (iii) a reduced ability to maintain Na+ homeostasis in the transgenic poplars during long-term salt stress, leading to their lowered ability to tolerate salinity stress. [ABSTRACT FROM AUTHOR]

Understanding the effect of glass network structure on the solubility properties of bioactive glasses is fundamental for designing new compositions with tailored biological functions and applications. This paper bridged the composition-structure-property relationship utilizing experimental measurements and molecular dynamics simulations. The Sr atom reorganized the network structures through a partial transformation of tetrahedral to trigonal boron units and the change of the ratio of bridged oxygen/non-bridged oxygen, which modified the glass structures at longer lengths scales, such as through changing the ring size distribution. Our results demonstrated that the evolution of solubility properties can be linked to the atomic structure change in short- and medium-range ordering. The structure-property relationship can be used to design and tune bioactive glass composition with specific properties. [Display omitted] [ABSTRACT FROM AUTHOR]

The extensive involvement of blowing in ablation and transpiration cooling directly influences the hypersonic boundary layer (HBL) transition. This work investigates the coupled effect of stabilization through micro-blowing and the corresponding porous blowing medium on a Mach 6 HBL flow. Linear stability theory (LST) and the eN method are used to interpret the characteristics of stability, and direct numerical simulations are used to resolve the detailed flow field among the porous microstructures to verify the predictions of LST. The sole effect of micro-blowing is first investigated by emphasizing the locations of the blowing strip. The results show that micro-blowing alone can significantly excite the first mode but stabilize the second mode. In general, the HBL becomes unstable if the blowing strip is installed upstream of the synchronization points of the dominant disturbances, and otherwise becomes stable. In the context of the blowing medium, a porous coating can suppress high-frequency disturbances and help stabilize the HBL if the blowing strip is placed upstream of the synchronization points of the dominant disturbances. On the contrary, the coating can prematurely excite lower-frequency disturbances and degrade the overall stabilization when the strip is located in the dominant region of the second mode. [ABSTRACT FROM AUTHOR]

• Reconstructed the phylogenetic relationship of the Syrphidae based on the different datasets of mitogenomes, and analysed and discussed the topological structures among different tribes. • Hoverfly genus Rhingia is resulted in a monophyletic group. • Natural selection, rather than mutation pressure, is exposed the main impact factor for codon usage bias in Rhingia. • It has strong AT bias in the nucleotide composition and optimal codons within Rhingia. • There are three optimal codons, GUU, ACU, and GGA, which are common to all five species of Rhingia. This study presents the sequencing and annotation of mitochondrial genomes from five Rhingia species of the family Syrphidae, focusing on codon bias. Each species possessed 22 tRNAs genes, 13 protein-coding genes, 2 rRNAs genes, and a control region, without any observed gene rearrangements. Nucleotide composition analysis revealed a higher AT content compared with GC content, indicating AT enrichment. Neutrality plot, Parity rule 2 bias, and effective number of codons plot analyses collectively indicated that natural selection primarily influences the codon usage bias in the five Rhingia species. Relative synonymous codon usage analysis identified the optimal codons for Rhingia binotata , R. fromosana , R. campestris , R. louguanensis , and R. xanthopoda as 10, 14, 10, 11, and 12, respectively, all ending with A/U and exhibiting AT preference. Phylogenetic analysis, based on maximum likelihood and Bayesian inference methods applied to three datasets, confirmed the monophyly of Rhingia. In conclusion, this research establishes a foundation for understanding the phylogenetic evolution and codon usage patterns in Rhingia , offering valuable for future studies. [ABSTRACT FROM AUTHOR]

• The most active catalyst, featuring Pt decoration on the Ni surface, activated within the first 10 h and preserved its activity over a 48-hour aging process. • CNTs on the Pt-Ni bimetallic catalyst showed a tendency to develop and migrate towards the support, displaying an increasing number of structural defects without entirely covering the metal active sites. • In contrast, the Ni/Al 2 O 3 catalyst experienced the accumulation of crystalline, low-defect CNTs, which enveloped Ni active sites over time, leading to rapid deactivation. Deactivation induced by coke deposition remains the foremost challenge in using Ni-based catalysts for the production of syngas via dry reforming of methane (DRM) reaction. Herein, highly dispersed Pt-Ni/Al 2 O 3 bimetallic catalysts prepared by atomic layer deposition (ALD) displayed remarkable stability at 650 ℃ in the DRM reaction. The Pt-Ni catalysts underwent an activation process within the initial 10 h and maintained its activity without deactivation throughout the subsequent aging testing up to 48 h. In contrast, the Ni/Al 2 O 3 rapidly deactivated over time. Despite its high CH 4 conversion rates, the Pt-Ni bimetallic catalyst produced a substantial quantity of carbon nanotubes (CNTs) analogous to the Ni/Al 2 O 3 catalyst. The discrepancy in stability performance between two catalysts derived from disparities in the carbon sites and structural defects evolving over reaction time. Regarding the catalysts with Pt decoration on the Ni surface, CNTs exhibited increasing structural defects and gradually deposited on the Al 2 O 3 support without fully encapsulating the metal active sites, as evidenced by CH 4 -TPD experiments. In the case of Ni nanoparticles on Al 2 O 3 , crystalline CNTs with fewer defects accumulated, leading to rapid deactivation. These findings enhance our understanding of coke resistance in DRM catalysts and help the development of more robust bimetallic catalyst systems. [ABSTRACT FROM AUTHOR]

Copper metal is essential to our production process, but it is highly corrosive in an ammonia environment and must be highly valued. Anti-corrosion coating is a simple and cost-effective method of preventing metal corrosion. In this study, a composite silane coating was prepared on copper using an impregnation method with mercaptopropyltriethoxysilane (TPTES) as the silane substrate and graphene oxide (GO) modified with isophorone diisocyanate (IPDI) or isocyanatopropyltriethoxysilane (IPTS) as filler to protect the copper from ammonia corrosion. The coating samples were hanging tested against ammonia corrosion by setting up two corrosive environments: ammonia gas and ammonia water. After 20 days of corrosion, the surfaces of the TPTES/IPDI-GO and TPTES/IPTS-GO coatings remained unchanged under both ammonia environments and the corrosion rate was consistently low at 2–3 μm/y. Additionally, the coating exhibited high protective qualities according to the electrochemical impedance spectroscopy (EIS) test in a 3.5% NaCl solution, which is attributed to the good dispersion that improves the densification and regularity of the coating. Meanwhile, IPTS-GO has a greater binding force with the coating matrix due to the increased number of reactive sites, resulting in further improved corrosion protection. This study provides an idea for research on ammonia-resistant coatings. [Display omitted] • Silane coatings are prepared by a simple impregnation method, with a simple process and wide range of applications. • 2、The corrosion hanging test was set up with two corrosive environments: ammonia gas and ammonia water. • 3、TPTES/IPDI-GO and TPTES/IPTS-GO silane coating samples show good protection after 20 days of corrosion in ammonia environments. • 4、 Further enhancement of the coating's ammonia corrosion resistance by increasing the number of reaction sites around the GO that are more readily available for binding to the coating substrate. [ABSTRACT FROM AUTHOR]

Transmembrane 9 superfamily proteins (TM9SFs) define a highly conserved protein family, each member of which is characterized by a variable extracellular domain and presumably nine transmembrane domains. Although previous studies have delineated the potential cytological roles of TM9SFs like autophagy and secretory pathway, their functions during development are largely unknown. To establish the basis for dissecting the functions of TM9SFs in vivo , we employed the open-source database, structure prediction, immunofluorescence and Western blot to describe the gene and protein expression patterns of TM9SFs in human and mouse. While TM9SFs are ubiquitously and homogeneously expressed in all tissues in human with RNA sequencing and proteomics analysis, we found that all mice Tm9sf proteins are preferentially expressed in lung except Tm9sf1 which is enriched in brain although they all distributed in various tissues we examined. In addition, we further explored their expression patterns in the mice central nervous system (CNS) and its extension tissue retina. Interestingly, we could show that Tm9sf1is developmentally up-regulated in brain. In addition, we also detected all Tm9sf proteins are located in neurons and microglia instead of astrocytes. Importantly, Tm9sf3 is localized in the nuclei which is distinct from the other members that are dominantly targeted to the plasma membrane/cytoplasm as expected. Finally, we also found that Tm9sf family members are broadly expressed in the layers of INL, OPL, and GCL of retina and likely targeted to the plasma membrane of retinal cells. Thus, our data provided a comprehensive overview of TM9SFs expression patterns, illustrating their ubiquitous roles in different organs, implying the possible roles of Tm9sf2/3/4 in lung functions and Tm9sf1 in neurodevelopment, and highlighting a unique cell biological functions of TM9SF3 in neuronal and microglia. [ABSTRACT FROM AUTHOR]

• The differences in interaction strength between AOEMIMTFSI and DMSO/CH 3 OH/CH 3 CN are described in detail. • The changes of hydrogen bonding interactions was unveiled. • Several complexes were assigned by excess spectra. Scientific research has witnessed an increasing fascination with ester-functionalized ionic liquids in recent years. These ester-functionalized ionic liquids are particularly attractive due to their superior biodegradability and potential applications, which surpass those of traditional ionic liquids. In actual use, it is common to blend these ionic liquids with co-solvents. However, there is currently a lack of research on the structures and interaction mechanisms of these mixtures. In this work, the hydrogen bonding interactions and microstructures of 1-acetoxyethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (AOEMIMTFSI) with various polar co-solvents (DMSO, CH 3 OH, CH 3 CN) were researched by combining infrared experiments and DFT calculations. The finding are as follows: (1) O atom in [TFSI]− primary interacts with C2−H in [AOEMIM]+, while the O or N atom in the co-solvents (DMSO, CH 3 OH, CH 3 CN) primarily interact with C4,5−H in [AOEMIM]+. (2) With the addition of co-solvents (DMSO‑ d 6 , CD 3 OD or CD 3 CN), the hydrogen bonding interactions associated with the v (imidazolium C−H) in the AOEMIMTFSI−DMSO‑ d 6 /CD 3 OD/CD 3 CN systems are strengthened. (3) The hydrogen bonding interactions between AOEMIMTFSI and DMSO are the strongest, followed by those between AOEMIMTFSI and CH 3 OH, while the hydrogen bonding interactions between AOEMIMTFSI and CH 3 CN are the weakest. (4) 2[AOEMIM]+[TFSI]−, 2[AOEMIM]+[TFSI]−−co-solvent, [AOEMIM]+[TFSI]−−co-solvent and [AOEMIM]+−co-solvent complexes were assigned through the analysis of excess spectra. [ABSTRACT FROM AUTHOR]

Transition metal cobalt doped BiOBr (Co-BOB) was successfully synthesized by using hydrothermal method. The optimized Co-BOB achieved a remarkable rhodamine B degradation rate of 97 % in 30 min under visible light irradiation when initial concentration was 80 mg·L−1. Satisfactory removal efficiency was also observed under ambient sunlight irradiation and various water conditions. The cobalt doping strategy induced abundant surface oxygen vacancies formation (43.22 %) and resulted in an increasing exposure of {110} facets. The photosensitization and photocatalytic activities of Co-BOB significantly enhanced comparing with that of pure BiOBr. The synergy of Co doping and oxygen vacancies also induced the formation of a new band structure in Co-BOB. The synergistic effect promoted the efficient separation of photogenerated electrons and holes. By combining with density functional theory calculation, the RhB photocatalytic degradation mechanism by Co-BOB was proposed. [Display omitted] • Trace amounts of cobalt contributed to the formation of abundant surface oxygen vacancies in BOB. • The photocatalytic degradation efficiency of Co-BOB under visible light irradiation achieved 97 % for 80 mg·L−1 RhB solution. • DFT calculation indicated that the mid-energy levels of Co-BOB were induced by cobalt atoms and oxygen vacancies. [ABSTRACT FROM AUTHOR]

Finer resolution is one of the development trends in ocean surface waves simulation and forecasting. However, high-resolution numerical models for ocean surface waves have led to an enormous increase in computational complexity, posing a challenge with respect to balancing computational efficiency and timeliness. To meet the demand for refined ocean surface waves simulation/forecasting and to address the computational efficiency challenge of high-resolution ocean surface waves models, we propose a downscaling model called the Global location-Specific transformation Downscaling Network (GSDNet) based on the non-autoregressive fusion network (NAFNet). By incorporating global location-specific transformation and introducing a land–sea distribution indicator, GSDNet can quickly and accurately map low-resolution significant wave heights to high-resolution grids. The results show that, compared with traditional interpolation methods such as the bilinear, inverse distance weight interpolation (IDW), and bicubic methods, the GSDNet model can reduce the global mean absolute error (MAE) by >77%. Compared with those of FourCastNet (FCN), the Koopman neural operator (KNO), the original NAFNet, and residual networks in deep learning from empirical downscaling methods (DL4DS_ResNet), the MAE decreases by >21%. Furthermore, the GSDNet model outperforms the other downscaling methods at the coastal boundary and for identifying the maximum significant wave height. In this work, we provide an effective solution for balancing computational efficiency and timeliness, which is important for improving the accuracy and reliability of ocean surface waves simulation/forecasting. • GSDNet demonstrates excellent downscaling ability for global wave heights. • GS is designed to capture fine features in margin regions. • GSDNet has a good generalization to apply in different resolutions via fine-tuning. [ABSTRACT FROM AUTHOR]

By considering the effects of the hygro-thermo-electro-magnetic environments, von Karman nonlinear terms, and multi-harmonic excitations, a coupled nonlinear vibration modeling of composite cylindrical shells comprising a carbon nanotube-reinforced composite (CNTRC) core and two piezoelectric/magnetic composite (PEMC) skins is developed, and the nonlinear dynamic behaviors of such cylindrical shells under primary, super/sub-harmonic, and combined resonance states are investigated. In the theoretical modeling process, the effective mechanical properties of the CNTRC core are first determined using the mixing and Schapery laws, and the hygro-thermo-electro-magneto-mechanical constitutive relations of the PEMC skins are then formulated. Within the framework of Reissner-Mindlin shell theory, the Lagrangian of the system containing Green-Lagrange and von Karman nonlinear terms is derived, and solution techniques based on the multiscale method are provided to obtain nonlinear frequencies, dynamic responses, and phases of CNTRC-PEMC cylindrical shells under multi-physics fields. Consequently, comparison studies are conducted to validate the correctness of the proposed model from different aspects. Based on this, various resonance and chaos behaviors of such structures subjected to multiple load components are revealed and compared, and the influences of environmental factors and structure composition on the amplitude-frequency curves, time-history responses, and phase planes are explored, with several recommendations and findings being drawn. [ABSTRACT FROM AUTHOR]

Background: Studies increasingly recognize the role of N6-methyladenosine (m6A) modification in cancer occurrence and development. METTL3 is a core catalytic subunit of m6A-modified methyltransferases complex, but its regulatory mechanism in ovarian cancer (OC) is not clear. Methods: In this study, GEPIA 2.0 database was applied for expression analysis, survival analysis and correlation analysis for OC. Additionally, in vitro and in vivo assays were conducted to explore regulatory mechanisms of METTL3 in OC. Results: We found that METTL3 and MALAT1 were significantly overexpressed in OC tissues and cells compared to normal ovarian tissues and cells. The proliferation rate of OC cells was reduced significantly after knocking down the expression of METTL3 or MALAT1. Subsequently, MALAT1 as oncogene was found to interact with METTL3 and was upregulated in OC tissues and cells. Silencing MALAT1 inhibited OC cell proliferation. Further studies indicated that METTL3 enhanced the stability of MALAT1 by promoting the m6A modification of MALAT1 and that ELAVL1 as a downstream binding protein significantly up-regulated MALAT1 expression. Conclusion: In conclusion, METTL3 was a carcinogenic molecule that promoted the occurrence of OC. The potential mechanism of the carcinogenic effect of METTL3 was realized by enhancing the m6A modification of MALAT1 mRNA through RNA binding protein ELAVL1. [ABSTRACT FROM AUTHOR]

The introduced Cr 3 C 2 phase into FeNi alloys suppress the thermal coarsening of alloy nanoparticles and induce the charge rearrangement around interface, thereby increasing the number of active sites and intrinsic activity of per sites, respectively. [Display omitted] Exploring high active electrocatalysts for oxygen evolution reaction (OER) is of great significance for a sustainable hydrogen economy. The development of non-precious transition metals, with sufficient active sites and ample intrinsic activity, remains a challenge. Herein, a new type of FeNi–Cr 3 C 2 heterostructure anchored on carbon sheets (FeNi–Cr 3 C 2 @C) was reported, which can effectively catalyze OER with swift kinetics and outstanding intrinsic activity. The introduced Cr 3 C 2 phase not only serves as a support material but also effectively suppresses the thermal coarsening of FeNi alloy nanoparticle. The FeNi–Cr 3 C 2 @C displays a robust OER activity with a low overpotential of 283 mV at the current density of 10 mA cm−2, a high turnover frequency value of 1.69 s−1 at the overpotential of 300 mV (10 times higher than that of FeNi@C) and good stability in alkaline media. Density functional theory calculations (DFT) calculations show that Cr 3 C 2 can facilitate the generation of electron-rich region at the Ni site in FeNi alloys as an active site, exhibiting an optimized adsorption behavior toward oxygen intermediate species with regard to decreased thermodynamic energy barriers. Our work opens up a promising path to modulate the electrocatalytic active sites using inexpensive and durable Cr 3 C 2 for electrochemical catalytic reactions. [ABSTRACT FROM AUTHOR]

The meso‐structure of pervious concrete significantly influences its overall performance. Accurately identifying the meso‐structure of pervious concrete is imperative for optimizing the design of pervious concrete, considering its mechanical properties and functionality. Therefore, to address the difficulty of recognizing the meso‐structures of pervious concrete, a method utilizing deep learning image semantic segmentation techniques is proposed in this study. First, based on the classical deep learning model, three models, namely, Res‐UNet, ED‐SegNet, and G‐ENet, are proposed for recognizing pervious concrete meso‐structure using deep learning image semantic segmentation techniques. These models introduce a residual module, a hybrid loss function, and a differential recognition branching structure to enhance the ability to recognize detailed information within pervious concrete meso‐structure and small targets. Second, the respective recognition performances of these methods on the meso‐structure of pervious concrete were thoroughly analyzed by experiment. The results indicate that the proposed three recognition methods for recognizing the meso‐structure of permeable concrete outperform conventional techniques not only in terms of efficiency but also in recognition accuracy and the ability to distinguish and identify aggregates, pores, and cement binders. In terms of comprehensive recognition effectiveness, the Res‐UNet model outperforms, followed by ED‐SegNet and G‐ENet. Furthermore, the computational efficiency of these three recognition methods meets the requirements of engineering applications. [ABSTRACT FROM AUTHOR]

Summary Rare variants contribute significantly to the ‘missing heritability’ of quantitative traits. The genome‐wide characteristics of rare variants and their roles in environmental adaptation of woody plants remain unexplored. Utilizing genome‐wide rare variant association study (RVAS), expression quantitative trait loci (eQTL) mapping, genetic transformation, and molecular experiments, we explored the impact of rare variants on stomatal morphology and drought adaptation in Populus. Through comparative analysis of five world‐wide Populus species, we observed the influence of mutational bias and adaptive selection on the distribution of rare variants. RVAS identified 75 candidate genes correlated with stomatal size (SS)/stomatal density (SD), and a rare haplotype in the promoter of serine/arginine‐rich splicing factor PtoRSZ21 emerged as the foremost association signal governing SS. As a positive regulator of drought tolerance, PtoRSZ21 can recruit the core splicing factor PtoU1‐70K to regulate alternative splicing (AS) of PtoATG2b (autophagy‐related 2). The rare haplotype PtoRSZ21hap2 weakens binding affinity to PtoMYB61, consequently affecting PtoRSZ21 expression and SS, ultimately resulting in differential distribution of Populus accessions in arid and humid climates. This study enhances the understanding of regulatory mechanisms that underlie AS induced by rare variants and might provide targets for drought‐tolerant varieties breeding in Populus. [ABSTRACT FROM AUTHOR]

Background: Sarcopenia is highly prevalent among patients with colorectal cancer (CRC). Computed tomography (CT)‐based assessment of low skeletal muscle index (SMI) is widely used for diagnosing sarcopenia. However, there are conflicting findings on the association between low SMI and overall survival (OS) in CRC patients. The objective of this study was to investigate whether CT‐determined low SMI can serve as a valuable prognostic factor in CRC. Methods: We collected data from patients with CRC who underwent radical surgery at our institution between June 2020 and November 2021. The SMI at the third lumbar vertebra was calculated using CT scans, and the cutoff values for defining low SMI were determined using receiver operating characteristic curves. Univariate and multivariate analyses were performed to assess the associations between clinical characteristics and postoperative major complications. Results: A total of 464 patients were included in the study, 229 patients (46.7%) were classified as having low SMI. Patients with low SMI were older and had a lower body mass index (BMI), a higher neutrophil to lymphocyte ratio (NLR), and higher nutritional risk screening 2002 (NRS2002) scores compared to those with normal SMI. Furthermore, patients with sarcopenia had a higher rate of major complications (10.9% vs. 1.3%; p < 0.001) and longer length of stay (9.09 ± 4.86 days vs. 8.25 ± 3.12 days; p = 0.03). Low SMI and coronary heart disease were identified as independent risk factors for postoperative major complications. Moreover, CRC patients with low SMI had significantly worse OS. Furthermore, the combination of low SMI with older age or TNM stage II + III resulted in the worst OS in each subgroup analysis. Conclusions: CT‐determined low SMI is associated with poor prognosis in patients with CRC, especially when combined with older age or advanced TNM stage. [ABSTRACT FROM AUTHOR]

This study constructs a model for the rapid identification of the origins of edible sunflower (Helianthus) using Kernel Extreme Learning Machine (KELM) with multi-source information fusion technology. Near-infrared spectroscopy (NIRS) and nuclear magnetic resonance spectroscopy (NMRS) were utilized to analyze 180 sunflower samples from the Xinjiang, Heilongjiang, and Inner Mongolia regions. Initially, the identification models for the origin of sunflowers using NIR and NMR data were compared between two algorithms: the Extreme Learning Machine (ELM) and KELM, combined with various spectral preprocessing methods. The experiment found that the NIR spectral model preprocessed with standard normal variate (SNV) using the KELM algorithm was the most accurate, achieving accuracies of 98.7% in the training set and 97.2% in the test set. The spin-echo NMR spectral model preprocessed with non-local means (NLMs) using the KELM algorithm was the second best, with accuracies of 98.4% in the training set and 96.4% in the test set. To further improve the accuracy of the identification models, innovative sunflower origin identification models were developed based on data layer fusion and feature layer fusion using NIRS and NMRS. In the data layer fusion model, the KELM algorithm model was optimal, achieving a test set accuracy and F1 score of 98.2% and 98.18%, respectively, an improvement of 1.0% over the best single data source model. In the feature layer fusion model, four types of feature-layer information-fusion identification models were established using two feature extraction algorithms, Competitive Adaptive Reweighted Sampling (CARS) and Variable Importance Projection (VIP), combined with joint feature and simple merging feature strategies. The CARS-KELM algorithm combined with the joint feature method was found to be the best, achieving 100% accuracy in both the training and test sets, an improvement of 2.8% over the best single data source model. Identifying the origin of edible sunflower using NIRS and NMRS is demonstrated as feasible by the results. The best single-spectrum sunflower origin identification model was achieved using the KELM algorithm with SNV preprocessing. The feature layer fusion method combining NIRS and NMRS data is suitable for handling the task of sunflower origin identification. This method significantly improves the recognition accuracy of the model compared to a single model, achieving fast and accurate origin identification of edible sunflowers. The research results provide a new method for rapid identification of sunflower origin. [ABSTRACT FROM AUTHOR]

Russula is the largest genus in the Russulales and is widespread throughout the world. Almost all Russula species are known to be ectomycorrhizal with high ecological and edible values, and some are lethal poisonous. In this study, four new species belonging to the subgenus Russula crown clade are identified based on morphological and phylogenetic evidence from the Xizang Autonomous Region and other provinces of China. Morphologically, Russula paragraveolens (sect. Polychromae, subsect. Xerampelinae) is mainly characterised by a cherry red to blood red pileus centre, a reddish orange pileus margin; R. pseudograveolens (sect. Polychromae, subsect. Xerampelinae) is characterised by a violet brown to brownish red pileus centre, a pale red to pastel red pileus margin and short basidia; R. shigatseensis (sect. Flavisiccantes, subsect. Lepidinae) is characterised by a brownish orange to madder red pileus centre, pinkish red pileus margin, and having lateral branches or branches of hyphal terminations in pileipellis; R. yadongensis (sect. Tenellae, subsect. Laricinae) is characterised by a dark purplish red pileus centre with brownish purple tints and having isolated to clustered spines of spore ornamentations. Their distinct taxonomic status is confirmed by the positions of the four new species in both the ITS and 4-locus (nucLSU, mtSSU, rpb2, tef1) phylogenetic trees. [ABSTRACT FROM AUTHOR]

Efficient adsorbents for excess bilirubin removal are extremely important for the treatment of hyperbilirubinemia. However, traditional adsorbents, such as activated carbons and ion-exchange resins, still suffer from dissatisfactory adsorption performance and poor blood compatibility. Herein, we adopted a rational design strategy guided by density functional theory (DFT) calculations to prepare blood-compatible quaternary ammonium group grafted electrospun polyacrylonitrile nanofiber adsorbents. The calculation analysis and adsorption experiments were used to investigate the structure–function relationship between group types and bilirubin adsorption, both indicating that quaternary ammonium groups with suitable configurations played a crucial role in bilirubin binding. The obtained nanofiber adsorbents showed the bilirubin removal efficiency above 90% even at a coexisting BSA concentration of 50 g L−1. The maximum adsorption capacities were 818.9 mg g−1 in free bilirubin solution and 163.7 mg g−1 in albumin bound bilirubin solution. The nanofiber adsorbents also showed considerable bilirubin removal in dynamic adsorption to reduce the bilirubin concentration to a normal level, which was better than commercial activated carbons. Our study demonstrates the high feasibility of a theory-driven design method for the development of grafted electrospun nanofibers, which have good potential as bilirubin adsorbents in hemoperfusion applications. [ABSTRACT FROM AUTHOR]

As an enhanced version of standard CAN, the Controller Area Network with Flexible Data (CAN-FD) rate is vulnerable to attacks due to its lack of information security measures. However, although anomaly detection is an effective method to prevent attacks, the accuracy of detection needs further improvement. In this paper, we propose a novel intrusion detection model for the CAN-FD bus, comprising two sub-models: Anomaly Data Detection Model (ADDM) for spotting anomalies and Anomaly Classification Detection Model (ACDM) for identifying and classifying anomaly types. ADDM employs Long Short-Term Memory (LSTM) layers to capture the long-range dependencies and temporal patterns within CAN-FD frame data, thus identifying frames that deviate from established norms. ACDM is enhanced with the attention mechanism that weights LSTM outputs, further improving the identification of sequence-based relationships and facilitating multi-attack classification. The method is evaluated on two datasets: a real-vehicle dataset including frames designed by us based on known attack patterns, and the CAN-FD Intrusion Dataset, developed by the Hacking and Countermeasure Research Lab. Our method offers broader applicability and more refined classification in anomaly detection. Compared with existing advanced LSTM-based and CNN-LSTM-based methods, our method exhibits superior performance in detection, achieving an improvement in accuracy of 1.44% and 1.01%, respectively. [ABSTRACT FROM AUTHOR]

Purpose: To compare the morphometry of paraspinal muscles in patients with degenerative spondylolisthesis (DS), isthmic spondylolisthesis (IS), and healthy individuals. Methods: Thirty-seven pairs of DS patients were selected using propensity score matching with IS patients, while 37 healthy individuals matched for age, sex, and BMI were selected as controls. The relative cross-sectional area (rCSA), and relative functional cross-sectional area (rfCSA) of paraspinal muscles were measured, and the degree of fatty infiltration (FI) was calculated. Based on occupational differences, the patients were also divided into worker and farmer groups, and the same measurements were taken on them. Results: At the L3/L4 level, the multifidus (MF) FI was greater in the DS and IS groups than in the control group, the erector spinae (ES) rfCSA was higher in the IS group than in the DS and control groups. At the L4/L5 level, MF rfCSA was smaller in the DS and IS groups than in the control group; ES rfCSA was higher in the IS group than in the DS and control groups. At the L5/S1 level, MF rfCSA was smaller in the DS and IS groups than in the control group; ES rfCSA was higher in the IS group than in the DS group. At the L3/L4, L4/L5 level, MF rfCSA were higher in the worker group than in the farmer group (p < 0.05). Conclusion: The morphological changes in paraspinal muscles in patients with DS were dominated by selective atrophy of the MF, while in patients with IS, the morphological changes in paraspinal muscle showed selective atrophy of the MF accompanied by compensatory hypertrophy of the ES. The surgeon should consider the morphological differences in paraspinal muscle between different types of lumbar spondylolisthesis when establishing the appropriate surgical program. [ABSTRACT FROM AUTHOR]

Predicting urban-scale carbon emissions (CEs) is crucial in drawing implications for various urgent environmental issues, including global warming. However, prior studies have overlooked the impact of the micro-level street environment, which might lead to biased prediction. To fill this gap, we developed an effective machine learning (ML) framework to predict neighborhood-level residential CEs based on a single data source, street view images (SVIs), which are publicly available worldwide. Specifically, more than 30 streetscape elements were classified from SVIs using semantic segmentation to describe the micro-level street environment, whose visual features can indicate major socioeconomic activities that significantly affect residential CEs. A ten-fold cross-validation was deployed to train ML models to predict the residential CEs at the 1 km grid level. We found, first, that random forest (R2 = 0.8) outperforms many traditional models, confirming that visual features are non-negligible in explaining CEs. Second, more building, wall, and fence views indicate higher CEs. Third, the presence of trees and grass is inversely related to CEs. Our findings justify the feasibility of using SVIs as a single data source to effectively predict neighborhood-level residential CEs. The framework is applicable to large regions across diverse urban forms, informing urban planners of sustainable urban form strategies to achieve carbon-neutral goals, especially for the development of new towns. [ABSTRACT FROM AUTHOR]

Introduction: The case fatality rate among patients with aneurysmal subarachnoid hemorrhage (aSAH) has decreased progressively, with numerous patients subjected to contemporary paradigms that minimize the use of agonizing therapeutic processes. The concept of the "Textbook Outcome" (TO), a composite outcome that highlights numerous favorable outcomes, was developed in the context of gastrointestinal tumor surgeries and expeditiously extended across diverse surgical spheres. The aim of this study was to explore the factors hindering the achievement of optimal prognoses in postinterventional aSAH patients, employ textbook outcomes, and establish predictive models. Methods: We conducted a retrospective review of data from 1270 aSAH patients who received endovascular treatment between 2012 and 2018. We delineated an exemplary TO within the aSAH domain, characterized by favorable clinical results, minimal complications, and the absence of retreatments. This TO-oriented approach is explained within the manuscript. Results: The findings revealed that preoperative intraventricular hemorrhage (IVH), preoperative Hunt and Hess grade (H&H) ≥ 3, World Federation of Neurosurgical Societies (WFNS) grade ≥ 3, the presence of blebs on the aneurysm, aneurysms situated at branching sites, and non-stent-assisted endovascular intervention were the strongest risk factors for not achieving textbook outcomes (non-"Textbook Outcome" [N-TO]). Decision curve analysis and calibration analyses revealed strong concordance between the predictions of the N-TO nomogram model and the actual observations. Conclusions: Treatment Outcomes hold significant practical value in clinical studies of aSAH patients receiving endovascular treatment. The likelihood of N-TOs was predicted by IVH, H&H grade ≥ 3, WFNS grade ≥ 2, presence o f bleb on the aneurysm, and aneurysms located at branching sites. [ABSTRACT FROM AUTHOR]

The accurate prediction of the future trajectories of traffic participants is crucial for enhancing the safety and decision-making capabilities of autonomous vehicles. Modeling social interactions among agents and revealing the inherent relationships is crucial for accurate trajectory prediction. In this context, we propose a goal-guided and interaction-aware state refinement graph attention network (SRGAT) for multi-agent trajectory prediction. This model effectively integrates high-precision map data and dynamic traffic states and captures long-term temporal dependencies through the Transformer network. Based on these dependencies, it generates multiple potential goals and Points of Interest (POIs). Through its dual-branch, multimodal prediction approach, the model not only proposes various plausible future trajectories associated with these POIs, but also rigorously assesses the confidence levels of each trajectory. This goal-oriented strategy enables SRGAT to accurately predict the future movement trajectories of other vehicles in complex traffic scenarios. Tested on the Argoverse and nuScenes datasets, SRGAT surpasses existing algorithms in key performance metrics by adeptly integrating past trajectories and current context. This goal-guided approach not only enhances long-term prediction accuracy, but also ensures its reliability, demonstrating a significant advancement in trajectory forecasting. [ABSTRACT FROM AUTHOR]

Background: Smoking remains a major risk factor for the development and progression of chronic obstructive pulmonary disease (COPD). Due to the adolescent smoking associated with worse health state, the age, at which an individual started smoking, might play a key role in shaping the trajectory of COPD development and the severity. Methods: We conducted an observational study from September 2016 through January 2023 of eligible patients hospitalized with COPD. Patients who started smoking during the alveolar development stage (ADS, smoking initiation ≤ 24 years old) were defined as early smoking patients, and patients who started smoking after ADS (smoking initiation > 24 years old) were defined as late smoking patients. We collected demographic and clinical data characterizing the patients and documented their condition from hospital discharge to follow-up. The primary endpoints were short-term (within one year), 3-year, and long-term (beyond 3 years) all-cause mortality after discharge. Results: Among 697 COPD patients, early smoking patients had a lower smoking cessation rate (P < 0.001) and a higher smoking index (P < 0.001) than late smoking patients. Although adjusted smoking index, early smoking patients still had poorer lung function (P = 0.023), thicker left ventricular diameters (P = 0.003), higher frequency of triple therapy use during stable stage (P = 0.049), and more acute exacerbations in the past year before enrollment (P < 0.05). Survival analysis showed that they had a higher risk of death after discharge within three years (P = 0.004) and beyond three years (P < 0.001). Furthermore, even in early smoking COPD patients who quit smoking after adjusting the smoking index had poorer lung function (P < 0.05) and thicker left ventricular diameters (P = 0.003), and survival analysis also showed that they had a higher long-term mortality rate (P = 0.010) and shorter survival time (P = 0.0128). Conclusion: Early smoking COPD patients exhibited multiple adverse clinical outcomes, including heavy cigarette addiction, compromised pulmonary function, augmented left ventricular diameter, and elevated mortality risk. Additional, smoking cessation could not bring enough improvement of health state in early smoking COPD patients as late smoking COPD patients. Consequently, early intervention and specialized cessation approaches for younger smokers are of paramount importance in this context. [ABSTRACT FROM AUTHOR]

Introduction: Psittacosis is a zoonosis caused by Chlamydia psittaci, the clinical manifestations of Psittacosis range from mild illness to fulminant severe pneumonia with multiple organ failure. This study aimed to evaluate the clinical characteristics of Chlamydia psittaci infection diagnosed based on metagenomic next-generation sequencing(mNGS), as well as the risk factors affecting the progress of Chlamydia psittaci infection, in order to improve the effect of therapeutics. Methods: We retrospectively analyzed the clinical data of patients infected with chlamydia psittaci in the First Affiliated Hospital of Nanchang University from January 2021 to December 2021. The patient's past medical history, clinical manifestations, laboratory examinations, chest CT results, treatment status, and prognosis data were collected. we also investigated both the pathogenic profile characteristics and the lower respiratory tract microbiota of patients with Chlamydia psittaci pneumonia using mNGS. Results: All cases of Chlamydia psittaci in our research have been confirmed by mNGS. Among 46 cases of Chlamydia psittaci pneumonia, Poultry exposure was reported in 35 cases. In severe cases of Chlamydia psittaci pneumonia, Neutrophils, Procalcitonin (PCT), Lactate Dehydrogenase (LDH), Hydroxybutyrate Dehydrogenase (HBDH), Creatine Kinase Isoenzymes-B (CK-MB) and D-Dimer levels were remarkably higher than that of non-severe cases, except for lymphocytes (all P < 0.05). Chest CT scans showed Bilateral (77.8%), multiple lobar lungs (85.2%), pleural effusions (44.4%) involvement in those suffering from severe Chlamydia psittaci pneumonia, whereas its incidence was 0%, 21.1% and 10.5% in non-severe patients, respectively (P < 0.05). Multivariate analysis revealed that higher lymphocyte concentrations (OR 0.836, 95% CI 0.714–0.962, P = 0.041) were the only protective factor for survival. mNGS results indicated that 41.3% of patients (19/46) had suspected coinfections with a coinfection rate of 84.2% (16/19) in the severe group, much higher than that in the non severe group (p < 0.05). No significantly different profiles of lower respiratory tract microbiota diversity were found between non severe group and severe group. Conclusion: A history of poultry exposure in patients can serve as an important basis for diagnosing Chlamydia psittaci pneumonia, and patients with severe Chlamydia psittaci pneumonia are more likely to develop elevated inflammatory biomarkers as well as elevated cardiac markers. Higher lymphocyte concentrations are protective factors associated with severe C. psittaci pneumonia. The higher proportion of patients with coinfections in our study supports the use of mNGS for comprehensive early detection of respiratory infections in patients with C. psittaci pneumonia. [ABSTRACT FROM AUTHOR]

The species of Gymnopilus (Hymenogastraceae, Agricales) are commonly recognized as wood-decaying fungi. Certain members of this genus have been identified as psilocybin-producing mushrooms. Gymnopilus exhibits a diverse range and has a global distribution. In this study, a total of seventy-eight specimens were gathered from ten provinces in China. A comprehensive molecular phylogenetic analysis was conducted, employing gene sequences including ITS, nrLSU, nrSSU, rpb1, rpb2, and tef1-α. Additionally, morphological examinations were also carried out. The phylogenetic topology of Gymnopilus from this study generally agreed with previous studies and facilitated the identification of all those specimens. As a result, eleven species, including five newly discovered ones named Gy. gyirongensis, Gy. variisporus, Gy. tomentosiceps, Gy. tenuibasidialis, and Gy. aurantipileatus, were recognized. Significantly, four of the five newly identified species are native to the Xizang Autonomous Region, emphasizing their specialization in this distinctive habitat. This research contributes to our comprehension of Gymnopilus diversity and lays the groundwork for the conservation and sustainable utilization of Gymnopilus resources. [ABSTRACT FROM AUTHOR]

This paper proposes a directly self-starting second-order s-sub-step explicit method, within which the three novel members are developed and analyzed for demonstration. The novel explicit schemes can output second-order accelerations for general structures, which cannot be achieved for the directly self-starting single- and two-sub-step algorithms. Each explicit algorithm achieves controllable algorithmic dissipation and adjustable bifurcation points. As a result, the novel explicit algorithms impose two algorithmic parameters, ρb and Ωb, to control numerical dissipation and bifurcation point, respectively. The parameter ρb, denoting the spectral radius at the bifurcation point, controls numerical dissipation, whereas the parameter Ωb, denoting the bifurcation point, adjusts the amount of dissipation imposed in the low-frequency range. This paper provides users with two recommended selections of Ωb. Apart from these desirable features, each novel explicit algorithm attains the maximum stability bound, 2 × s where s denotes the number of sub-steps. The four- and five-sub-step algorithms perform optimization to reduce numerical low-frequency dissipation. As the number of sub-steps increases, the novel explicit algorithms can have better numerical characteristics without an increase in the computational effort. Numerical examples are simulated to validate the performance and superiority of the novel explicit algorithms. [ABSTRACT FROM AUTHOR]

Chloride transport within concrete is critical for the durability of reinforced concrete structures; however, its diffusion under the coupling action of temperature and humidity has not been fully comprehended. Therefore, in this work, the coupling effects of temperature, relative humidity, and mineral admixtures on chloride transport in concrete were investigated through experimental and numerical simulation work. The results show that the chloride diffusion coefficient decreases with the decreased temperature and growth of relative humidity; however, the chloride concentration on the concrete surface is increased with the growth of temperature and relative humidity. Moreover, compounding about 15% fly ash (FA) and 30% granulated ground blast furnace slag (GGBS) to replace the cement is the most beneficial for improving the antichloride capacity of concrete, considering also the strength. In addition, the numerical simulation considering the coupled effect of temperature and relative humidity of chloride transport in concrete has good agreement with that of experimental results. [ABSTRACT FROM AUTHOR]

[Display omitted] • The structure of MnOx@aTiOy showed the increasing capacity being activated to maintain for a long-term cycling (829.5 mAh g−1 at 1 A g−1 after 2000 cycles). • The oxygen defects in the coating layer of modified TiO 2 boosted the pseudocapacitance effect for electrochemical performance. • The DFT calculations reveals the oxygen defects, the transformation of α-MnO 2 into Bixbyite-O Mn 2 O 3 , would decrease the kinetics of Li+ on lithium migrating paths and energy barriers. In this work, we developed Manganese and Titanium based oxide composites with oxygen defects (MnO x @aTiO y) via plasma processing as anodes of lithium ion batteries. By appropriately adjusting the defect concentration, the ion transport kinetics and electrical conductivity of the electrodes are significantly improved, showing stable capacity retention. Furthermore, the incremental capacity is further activated and long-term stable cycling performance is achieved, with a specific capacity of 829.5 mAh/g at 1 A/g after 2000 cycles. To scrutinize the lithium migration paths and energy barriers in MnO 2 and Mn 2 O 3 , the density functional theory (DFT) calculations is performed to explore the lithium migration paths and energy barriers. Although the transformation of MnO 2 into Mn 2 O 3 through oxygen defects was initially surmised to inhibit Li ions along their standard routes, our results indicate quite the contrary. In fact, the composite's lithium diffusion rate saw a substantial increase. This can be accredited to the pronounced enhancement of conductivity and ion transport efficiency in the amorphous and porous TiO y. [ABSTRACT FROM AUTHOR]

Head and neck squamous cell carcinoma (HNSCC) is a common malignant tumour. Despite advancements in surgery, radiotherapy and chemotherapy, which have improved the prognosis of most patients, a subset of patients with poor prognoses still exist due to loss of surgical opportunities, postoperative recurrence, and metastasis, among other reasons. The tumour microenvironment (TME) is a complex organization composed of tumour, stromal, and endothelial cells. Communication and interaction between tumours and immune cells within the TME are increasingly being recognized as pivotal in inhibiting or promoting tumour development. Previous studies on T cells in the TME of HNSCC have yielded novel therapeutic possibilities. However, the function of B cells, another adaptive immune cell type, in the TME of HNSCC patients has yet to be determined. Recent studies have revealed various distinct subtypes of B cells and tertiary lymphoid structures (TLSs) in the TME of HNSCC patients, which are believed to impact the efficacy of immune checkpoint inhibitors (ICIs). Therefore, this paper focuses on B cells in the TME to explore potential directions for future immunotherapy for HNSCC. [ABSTRACT FROM AUTHOR]

Background: Radiotherapy (RT) is an effective and available local treatment for patients with refractory or relapsed (R/R) aggressive B-cell lymphomas. However, the value of hypofractionated RT in this setting has not been confirmed. Methods: We retrospectively analyzed patients with R/R aggressive B-cell lymphoma who received hypofractionated RT between January 2020 and August 2022 at a single institution. The objective response rate (ORR), overall survival (OS), progression-free survival (PFS) and acute side effects were analyzed. Results: A total of 30 patients were included. The median dose for residual disease was 36 Gy, at a dose per fraction of 2.3–5 Gy. After RT, the ORR and complete response (CR) rates were 90% and 80%, respectively. With a median follow-up of 10 months (range, 2–27 months), 10 patients (33.3%) experienced disease progression and three died. The 1-year OS and PFS rates for all patients were 81.8% and 66.3%, respectively. The majority (8/10) of post-RT progressions involved out-of-field relapses. Patients with relapsed diseases, no response to systemic therapy, multiple lesions at the time of RT, and no response to RT were associated with out-of-field relapses. PFS was associated with response to RT (P = 0.001) and numbers of residual sites (P < 0.001). No serious non-hematological adverse effects (≥ grade 3) associated with RT were reported. Conclusion: These data suggest that hypofractionated RT was effective and tolerable for patients with R/R aggressive B-cell lymphoma, especially for those that exhibited localized residual disease. [ABSTRACT FROM AUTHOR]

Converting carbon dioxide into lower olefins (C 2 =-C 4 =) through hydrogenation is a crucial chemical reaction that allows for the use of CO 2 as carbon source in the production of foundational chemicals. Herein, nitrogen-doped carbon-coated iron-based catalysts were obtained by pyrolysis NH 2 -MIL-88B under N 2 atmosphere. The results show that the catalyst morphology, particle size and Fe phase structure can be controlled by changing the pyrolysis conditions. As the temperature rises, the structure starts to deteriorate, resulting in a gradual increase in the iron content and particle size. Fe 3 O 4 and Fe 3 C phases appeared in the 350/500 °C two-stage pyrolysis, and the two-stage pyrolysis could effectively alleviate the structural collapse of MOFs precursors during the pyrolysis process. With the catalyst obtained by 350/500 °C two-stage pyrolysis, the conversion of CO 2 could reach 35.1% and the selectivity of light olefins reached 37.7% (340 °C, 3 MPa, and GHSV= 5000 mL g cat −1 h−1). [Display omitted] • Nitrogen-doped carbon-coated iron-based catalysts were obtained by pyrolysis NH 2 -MIL-88B under N 2 atmosphere. • Different pyrolysis temperatures have significant impact on the structure and efficacy of catalysts. • Fe 3 O 4 -FeC x structure with high selectivity can be produced by two-step pyrolysis process. [ABSTRACT FROM AUTHOR]

This study investigates the impact of the expanded audit report on IPO underpricing. Using the sample of A-share listed firms in China from June 2014 to November 2021, we find that the expanded audit reports can reduce the speculative behavior of investors in the initial phase of IPOs, resulting in lower IPO underpricing and consecutive rising limits. The channel tests suggest that the disclosure of key audit matters reduces value uncertainty and alleviates investors' local bias. Our results are consistent to a series of robustness tests. Further analyses show that the negative relation between expanded audit reports and IPO underpricing intensifies when the legal environment is weak and firms' information transparency is low. Additional tests uncover positive market reaction after the mandatory disclosure rule in the long run. Overall, our study adds new insights to the information effects of the expanded audit reports in emerging markets. • The expanded audit reports reduce IPO underpricing and consecutive rising limits. • KAM reduces value uncertainty and alleviates investors' local bias. • The results are moderated by legal environment and information transparency. [ABSTRACT FROM AUTHOR]

[Display omitted] • The fabricated UIO-la-CoN-rGO aerogel possesses the properties of hydrophobic, anti-corrosion, heat insulation, infrared stealth and electromagnetic wave absorption. • The UIO-la-CoN-rGO aerogel achieves high EMW absorbing performance, with reflection loss of −44.8 dB and effective absorbing bandwidth (EAB) of 7.28 GHz. • The UIO-la-CoN-rGO aerogel shows an impedance value of 1.5 × 105 Ω·cm2 after being soaked in 3.5 % aqueous NaCl for 30 d with an anti-corrosion efficiency of 99.149 %. • The introduction of heteroatoms enriches the defect sites of the materials, thus increasing the interfacial polarization and dipole polarization. In addition to having a superior electromagnetic wave (EMW) absorption profile, materials of this type that are applied in complex and extreme environments must be hydrophobic, anti-corrosive, heat insulating and infrared stealth. In the described investigation, a multifunctional UIO-la-CoN-rGO aerogel that possesses all of these properties was fabricated by using a hydrothermal and freeze drying process. Lauric acid (la) is incorporated into this aerogel to enlarge pore sizes and enhance hydrophobicity of the Zr-based metal organic framework (UIO-66) component. The large interfacial and dipole polarization caused by anchoring UIO-66 nanospheres to the Co,N co-doped graphene nanosheets results in a high EMW absorbing performance, reflected in a minimum reflection loss (RL min) of −44.8 dB and a wide effective absorbing bandwidth (EAB) of 7.28 GHz. In addition, the aerogel displays high levels of hydrophobicity, anti-corrosiveness, heat insulation and infrared stealth. For example, UIO-la-CoN-rGO has a water contact angle of 142.5°and a surface temperature that remains nearly unchanged after more than 1 h at 100 ℃. Moreover, the UIO-la-CoN-rGO coating gives the aerogel an impedance value of 1.5 × 105 Ω·cm2 after being soaked in 3.5 % aqueous NaCl for 30 d, and an anti-corrosion efficiency of 99.149 %. The results of this study provide guidance for the design of multifunctional EMW absorbing materials that function in complex environments. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) plays a critical role in the prediction, planning, and control of autonomous vehicle. The original motion control methods are increasing in accuracy, but their control style markedly differs from that of human drivers. This not only degrades the passenger's ride experience but also brings unfamiliarity to other drivers, leading to safety hazards. Moreover, some of the methods are a direct application of AI techniques without any specific enhancements tailored for vehicle control. This both fails to fully utilize the potential of AI and reduces interpretability. To address these issues, in this paper, deep learning methods are integrated with driver control mechanisms to propose a human-like neural network for vehicle longitudinal dynamics estimation and control (HNN). First, the process of driver estimation and control of vehicle dynamics is proposed and described in mathematical language. Subsequently, the HNN composed of three sub-networks is presented. The three sub-networks correspond to the three sub-processes of the driver's mechanism, which makes the proposed HNN method more applicable to vehicle dynamics control and more interpretable in specific engineering domains. The effectiveness of the HNN method is verified on a real-world dataset. The results demonstrate that the HNN not only enhances vehicle human-like control but also surpasses baselines in terms of control style consistency and convergence rate. • The method is a deep integration of human control mechanisms and artificial intelligence in a specific engineering domain. • The proposed deep learning method has a unique structure derived from the driver control mechanism.The structure of the method makes it more applicable for vehicle motion control with active rule-based interpretability. • The tolerance control pattern is proposed and incorporated into the mechanism of driver control vehicle dynamics. • Compared to the baselines, the method proves to be more suitable for the engineering field of vehicle human-like control. [ABSTRACT FROM AUTHOR]

[Display omitted] • CuFe 2 O 4 /g-C 3 N 4 was prepared by secondary microwave co-precipitation. • Ferromagnetic resonance effect enhanced the oxidation property of CuFe 2 O 4 /g-C 3 N 4. • Adsorption effect of the catalyst in high-salinity environments was greatly promoted. • CuFe 2 O 4 /g-C 3 N 4 enabled 100 % removal of tetracycline from mariculture wastewater. • The photo-Fenton system would not impair the healthy growth of clownfish. Superior separation of photogenerated carriers holds the key to intensive degradation of tetracycline (TC) in mariculture wastewater under natural sunlight. CuFe 2 O 4 /g-C 3 N 4 (CFO/g) was synthesized by secondary microwave co-precipitation (SMCP) based on the ferromagnetic resonance absorption effect. Under the reaction conditions of pH = 6.5, CFO/g = 0.2 g/L, [H 2 O 2 ] = 1 mM, 99.0 % TC removal was realized in 40 min. Enhanced performance for TC removal in high-salinity environments heavily relied on elevated ionic strength and rapid electron transfer of CFO/g in conjunction with high-salinity interactions. To ecologically remediate mariculture wastewater under natural sunlight, we immobilized powdered CFO/g to a ferrite magnet and devised a continuous flow reaction apparatus, incorporating the controlled injection of hydrogen peroxide (H 2 O 2), to achieve the 100 % TC removal and simultaneously undertake the pretreatment of other contaminants (∼70 %). Ultimately, a safety assessment demonstrated that the degradation of mariculture wastewater by the CFO/g photo-Fenton system is a reliable and efficient technology, and the growth of clownfish remained unimpaired. SMCP successfully accelerated the conversion of high-valent metal ions to low-valent ones and eased the activation barriers of H 2 O 2 , enabling various active species to execute their respective roles productively. Innovative application of microwave resonance to enhance the magnetic properties of CFO/g and to support the equilibrium conversion of elemental valence states in high-salinity environments from real wastewater. [ABSTRACT FROM AUTHOR]

[Display omitted] • The fabricated FeNi-MOF-rGO aerogels exhibits remarkable EMW absorption performances with strong RL and broad EAB at the thickness of 2.9 mm (−48.3 dB and 8.32 GHz) whereas the filling contents are just 5 %. • The morphology and structure of MOF are regulated by electron transfer of GO and the obtained MOF with unique strip or regular octahedral shape results in vast heterojunction interfaces. • The electron transfer was further confirmed by DFT differential density and Bader charge analysis and the interfacial polarization of the material was confirmed by finite element simulation. Graphene and its derivatives have become the star materials in the field of electromagnetic wave (EMW) absorption, and have been widely studied because of their unique structure and excellent properties. However, the high electrical conductivity of graphene-based material leads to poor impedance matching performances, so it often needs to be annealed at high temperatures, which is a intricate procedure and cause the waste of energy. Herein, we develop a convenient strategy to synthesize metal organic framework-reduced graphene oxide (MOF-rGO) aerogels through facile hydrothermal and freeze drying procedure. Firstly, the excessive electrons on graphene can be transferred to MOF, in this way, no annealing is needed. Secondly, the morphology and structure of MOF can be regulated electronically to endow the material with rich heterojunction interfaces and enhance its interfacial polarization. Thirdly, the synthesized aerogels satisfy the requirements of thin thickness, low density and light weight. The fabricated Ni-MOF-rGO and FeNi-MOF-rGO aerogels exhibit remarkable EMW absorption performances with strong reflection loss (RL) and broad effective absorption band (EAB) at the thickness of 2.4 (−47.8 dB and 7.84 GHz) and 2.9 mm (−48.3 dB and 8.32 GHz) whereas the filling contents are just 5 %. Moreover, the attenuation capacity of the fabricated aerogels are verified through the radar-section simulation and the interfacial polarization loss are confirmed by the COMSOL analogue simulation. In a word, this work provides a new afflatus and inspiration for the design of graphene-based EMW absorption materials. [ABSTRACT FROM AUTHOR]